Documentos donde el Tema es "Materias > Biomedicina"

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  - Biomedicina (64)

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Número de registros en este nivel: 64.

2024

Artículo Materias > Biomedicina Universidad Europea del Atlántico > Investigación > Producción Científica
Fundación Universitaria Internacional de Colombia > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Producción Científica
Universidad Internacional Iberoamericana Puerto Rico > Investigación > Artículos y libros
Universidad Internacional do Cuanza > Investigación > Producción Científica
Universidad de La Romana > Investigación > Producción Científica Abierto Inglés Emergency medical services (EMSs) face critical situations that require patient risk classification based on analytical and vital signs. We aimed to establish clustering-derived phenotypes based on prehospital analytical and vital signs that allow risk stratification. This was a prospective, multicenter, EMS-delivered, ambulance-based cohort study considering six advanced life support units, 38 basic life support units, and four tertiary hospitals in Spain. Adults with unselected acute diseases managed by the EMS and evacuated with discharge priority to emergency departments were considered between January 1, 2020, and June 30, 2023. Prehospital point-of-care testing and on-scene vital signs were used for the unsupervised machine learning method (clustering) to determine the phenotypes. Then phenotypes were compared with the primary outcome (cumulative mortality (all-cause) at 2, 7, and 30 days). A total of 7909 patients were included. The median (IQR) age was 64 (51–80) years, 41% were women, and 26% were living in rural areas. Three clusters were identified: alpha 16.2% (1281 patients), beta 28.8% (2279), and gamma 55% (4349). The mortality rates for alpha, beta and gamma at 2 days were 18.6%, 4.1%, and 0.8%, respectively; at 7 days, were 24.7%, 6.2%, and 1.7%; and at 30 days, were 33%, 10.2%, and 3.2%, respectively. Based on standard vital signs and blood test biomarkers in the prehospital scenario, three clusters were identified: alpha (high-risk), beta and gamma (medium- and low-risk, respectively). This permits the EMS system to quickly identify patients who are potentially compromised and to proactively implement the necessary interventions. metadata López-Izquierdo, Raúl; del Pozo Vegas, Carlos; Sanz-García, Ancor; Mayo Íscar, Agustín; Castro Villamor, Miguel A.; Silva Alvarado, Eduardo René; Gracia Villar, Santos; Dzul López, Luis Alonso; Aparicio Obregón, Silvia; Calderón Iglesias, Rubén; Soriano, Joan B. y Martín-Rodríguez, Francisco mail SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, eduardo.silva@funiber.org, santos.gracia@uneatlantico.es, luis.dzul@uneatlantico.es, silvia.aparicio@uneatlantico.es, ruben.calderon@uneatlantico.es, SIN ESPECIFICAR, SIN ESPECIFICAR (2024) Clinical phenotypes and short-term outcomes based on prehospital point-of-care testing and on-scene vital signs. npj Digital Medicine, 7 (1). ISSN 2398-6352

Artículo Materias > Biomedicina
Materias > Ciencias Sociales
Materias > Ingeniería Universidad Europea del Atlántico > Investigación > Producción Científica
Fundación Universitaria Internacional de Colombia > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Producción Científica
Universidad Internacional Iberoamericana Puerto Rico > Investigación > Artículos y libros
Universidad Internacional do Cuanza > Investigación > Producción Científica
Universidad de La Romana > Investigación > Producción Científica Abierto Inglés Aim: The development of predictive models for patients treated by emergency medical services (EMS) is on the rise in the emergency field. However, how these models evolve over time has not been studied. The objective of the present work is to compare the characteristics of patients who present mortality in the short, medium and long term, and to derive and validate a predictive model for each mortality time. Methods: A prospective multicenter study was conducted, which included adult patients with unselected acute illness who were treated by EMS. The primary outcome was noncumulative mortality from all causes by time windows including 30-day mortality, 31- to 180-day mortality, and 181- to 365-day mortality. Prehospital predictors included demographic variables, standard vital signs, prehospital laboratory tests, and comorbidities. Results: A total of 4830 patients were enrolled. The noncumulative mortalities at 30, 180, and 365 days were 10.8%, 6.6%, and 3.5%, respectively. The best predictive value was shown for 30-day mortality (AUC = 0.930; 95% CI: 0.919–0.940), followed by 180-day (AUC = 0.852; 95% CI: 0.832–0.871) and 365-day (AUC = 0.806; 95% CI: 0.778–0.833) mortality. Discussion: Rapid characterization of patients at risk of short-, medium-, or long-term mortality could help EMS to improve the treatment of patients suffering from acute illnesses. metadata Enriquez de Salamanca Gambara, Rodrigo; Sanz-García, Ancor; del Pozo Vegas, Carlos; López-Izquierdo, Raúl; Sánchez Soberón, Irene; Delgado Benito, Juan F.; Martínez Díaz, Raquel; Mazas Pérez-Oleaga, Cristina; Martínez López, Nohora Milena; Dominguez Azpíroz, Irma y Martín-Rodríguez, Francisco mail SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, raquel.martinez@uneatlantico.es, cristina.mazas@uneatlantico.es, nohora.martinez@uneatlantico.es, irma.dominguez@unini.edu.mx, SIN ESPECIFICAR (2024) A Comparison of the Clinical Characteristics of Short-, Mid-, and Long-Term Mortality in Patients Attended by the Emergency Medical Services: An Observational Study. Diagnostics, 14 (12). p. 1292. ISSN 2075-4418

Artículo Materias > Biomedicina
Materias > Ingeniería Universidad Europea del Atlántico > Investigación > Producción Científica
Fundación Universitaria Internacional de Colombia > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Producción Científica
Universidad Internacional Iberoamericana Puerto Rico > Investigación > Artículos y libros
Universidad de La Romana > Investigación > Producción Científica Abierto Inglés Non-Insulin-Dependent Diabetes Mellitus (NIDDM) is a chronic health condition caused by high blood sugar levels, and if not treated early, it can lead to serious complications i.e. blindness. Human Activity Recognition (HAR) offers potential for early NIDDM diagnosis, emerging as a key application for HAR technology. This research introduces DiabSense, a state-of-the-art smartphone-dependent system for early staging of NIDDM. DiabSense incorporates HAR and Diabetic Retinopathy (DR) upon leveraging the power of two different Graph Neural Networks (GNN). HAR uses a comprehensive array of 23 human activities resembling Diabetes symptoms, and DR is a prevalent complication of NIDDM. Graph Attention Network (GAT) in HAR achieved 98.32% accuracy on sensor data, while Graph Convolutional Network (GCN) in the Aptos 2019 dataset scored 84.48%, surpassing other state-of-the-art models. The trained GCN analyzed retinal images of four experimental human subjects for DR report generation, and GAT generated their average duration of daily activities over 30 days. The daily activities in non-diabetic periods of diabetic patients were measured and compared with the daily activities of the experimental subjects, which helped generate risk factors. Fusing risk factors with DR conditions enabled early diagnosis recommendations for the experimental subjects despite the absence of any apparent symptoms. The comparison of DiabSense system outcome with clinical diagnosis reports in the experimental subjects was conducted using the A1C test. The test results confirmed the accurate assessment of early diagnosis requirements for experimental subjects by the system. Overall, DiabSense exhibits significant potential for ensuring early NIDDM treatment, improving millions of lives worldwide. metadata Alam, Md Nuho Ul; Hasnine, Ibrahim; Bahadur, Erfanul Hoque; Masum, Abdul Kadar Muhammad; Briones Urbano, Mercedes; Masías Vergara, Manuel; Uddin, Jia; Ashraf, Imran y Samad, Md. Abdus mail SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, mercedes.briones@uneatlantico.es, manuel.masias@uneatlantico.es, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR (2024) DiabSense: early diagnosis of non-insulin-dependent diabetes mellitus using smartphone-based human activity recognition and diabetic retinopathy analysis with Graph Neural Network. Journal of Big Data, 11 (1). ISSN 2196-1115

Artículo Materias > Biomedicina
Materias > Ingeniería Universidad Europea del Atlántico > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Producción Científica
Universidad Internacional Iberoamericana Puerto Rico > Investigación > Artículos y libros
Universidad Internacional do Cuanza > Investigación > Producción Científica
Universidad de La Romana > Investigación > Producción Científica Abierto Inglés Objective Epileptic seizures are neurological events that pose significant risks of physical injuries characterized by sudden, abnormal bursts of electrical activity in the brain, often leading to loss of consciousness and uncontrolled movements. Early seizure detection is essential for timely treatments and better patient outcomes. To address this critical issue, there is a need for an advanced artificial intelligence approach for the early detection of epileptic seizure disorder. Methods This study primarily focuses on designing a novel ensemble approach to perform early detection of epileptic seizure disease with high performance. A novel ensemble approach consisting of a fast, independent component analysis random forest (FIR) and prediction probability is proposed, which uses electroencephalography (EEG) data to investigate the efficacy of the proposed approach for early detection of epileptic seizures. The FIR model extracts independent components and class prediction probability features, creating a new feature set. The proposed model combined integrated component analysis (ICA) with predicting probability to enhance seizure recognition accuracy scores. Extensive experimental evaluations demonstrate that FIR assists machine learning models to obtain superior results compared to original features. Results The research gap is addressed using combined features to improve the performance of epileptic seizure detection compared to a single feature set. In particular, the ensemble model FIR with support vector machine (FIR + SVM) outperforms other methods, achieving an accuracy of 98.4% for epileptic seizure detection. Conclusions The proposed FIR has the potential for early diagnosis of epileptic seizures and can significantly help the medical industry with enhanced detection and timely interventions. metadata Khalid, Madiha; Raza, Ali; Akhtar, Adnan; Rustam, Furqan; Brito Ballester, Julién; Rodríguez Velasco, Carmen Lilí; Díez, Isabel de la Torre y Ashraf, Imran mail SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, julien.brito@uneatlantico.es, carmen.rodriguez@uneatlantico.es, SIN ESPECIFICAR, SIN ESPECIFICAR (2024) Diagnosing epileptic seizures using combined features from independent components and prediction probability from EEG data. DIGITAL HEALTH, 10. ISSN 2055-2076

Artículo Materias > Biomedicina
Materias > Ingeniería Universidad Europea del Atlántico > Investigación > Producción Científica
Universidad Internacional Iberoamericana Puerto Rico > Investigación > Artículos y libros
Universidad Internacional do Cuanza > Investigación > Producción Científica Cerrado Inglés Brain–computer interface (BCI) technology holds promise for individuals with profound motor impairments, offering the potential for communication and control. Motor imagery (MI)-based BCI systems are particularly relevant in this context. Despite their potential, achieving accurate and robust classification of MI tasks using electroencephalography (EEG) data remains a significant challenge. In this paper, we employed the Minimum Redundancy Maximum Relevance (MRMR) algorithm to optimize channel selection. Furthermore, we introduced a hybrid optimization approach that combines the War Strategy Optimization (WSO) and Chimp Optimization Algorithm (ChOA). This hybridization significantly enhances the classification model’s overall performance and adaptability. A two-tier deep learning architecture is proposed for classification, consisting of a Convolutional Neural Network (CNN) and a modified Deep Neural Network (M-DNN). The CNN focuses on capturing temporal correlations within EEG data, while the M-DNN is designed to extract high-level spatial characteristics from selected EEG channels. Integrating optimal channel selection, hybrid optimization, and the two-tier deep learning methodology in our BCI framework presents an enhanced approach for precise and effective BCI control. Our model got 95.06% accuracy with high precision. This advancement has the potential to significantly impact neurorehabilitation and assistive technology applications, facilitating improved communication and control for individuals with motor impairments metadata Kumari, Annu; Edla, Damodar Reddy; Reddy, R. Ravinder; Jannu, Srikanth; Vidyarthi, Ankit; Alkhayyat, Ahmed y Garat de Marin, Mirtha Silvana mail SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, silvana.marin@uneatlantico.es (2024) EEG-based motor imagery channel selection and classification using hybrid optimization and two-tier deep learning. Journal of Neuroscience Methods, 409. p. 110215. ISSN 01650270

Artículo Materias > Biomedicina
Materias > Ingeniería
Materias > Alimentación Universidad Europea del Atlántico > Investigación > Producción Científica
Universidad Internacional Iberoamericana Puerto Rico > Investigación > Artículos y libros
Universidad Internacional do Cuanza > Investigación > Producción Científica Abierto Inglés Background and objectives: As microbes are developing resistance to antibiotics, natural, botanical drugs or traditional herbal medicine are presently being studied with an eye of great curiosity and hope. Hence, complementary and alternative treatments for uncomplicated pelvic inflammatory disease (uPID) are explored for their efficacy. Therefore, this study determined the therapeutic efficacy and safety of Sesamum indicum Linn seeds with Rosa damascena Mill Oil in uPID with standard control. Additionally, we analyzed the data with machine learning. Materials and methods: We included 60 participants in a double-blind, double-dummy, randomized standard-controlled study. Participants in the Sesame and Rose oil group (SR group) (n = 30) received 14 days course of black sesame powder (5 gm) mixed with rose oil (10 mL) per vaginum at bedtime once daily plus placebo capsules orally. The standard group (SC), received doxycycline 100 mg twice and metronidazole 400 mg thrice orally plus placebo per vaginum for the same duration. The primary outcome was a clinical cure at post-intervention for visual analogue scale (VAS) for lower abdominal pain (LAP), and McCormack pain scale (McPS) for abdominal-pelvic tenderness. The secondary outcome included white blood cells (WBC) cells in the vaginal wet mount test, safety profile, and health-related quality of life assessed by SF-12. In addition, we used AdaBoost (AB), Naïve Bayes (NB), and Decision Tree (DT) classifiers in this study to analyze the experimental data. Results: The clinical cure for LAP and McPS in the SR vs SC group was 82.85% vs 81.48% and 83.85% vs 81.60% on Day 15 respectively. On Day 15, pus cells less than 10 in the SR vs SC group were 86.6% vs 76.6% respectively. No adverse effects were reported in both groups. The improvement in total SF-12 score on Day 30 for the SR vs SC group was 82.79% vs 80.04% respectively. In addition, our Naive Bayes classifier based on the leave-one-out model achieved the maximum accuracy (68.30%) for the classification of both groups of uPID. Conclusion: We concluded that the SR group is cost-effective, safer, and efficacious for curing uPID. Proposed alternative treatment (test drug) could be a substitute of standard drug used for Female genital tract infections. metadata Sumbul, X.; Sultana, Arshiya; Heyat, Md Belal Bin; Rahman, Khaleequr; Akhtar, Faijan; Parveen, Saba; Briones Urbano, Mercedes; Lipari, Vivian; De la Torre Díez, Isabel; Khan, Azmat Ali y Malik, Abdul mail SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, mercedes.briones@uneatlantico.es, vivian.lipari@uneatlantico.es, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR (2024) Efficacy and classification of Sesamum indicum linn seeds with Rosa damascena mill oil in uncomplicated pelvic inflammatory disease using machine learning. Frontiers in Chemistry, 12. ISSN 2296-2646

Artículo Materias > Biomedicina Universidad Europea del Atlántico > Investigación > Producción Científica
Universidad Internacional Iberoamericana Puerto Rico > Investigación > Artículos y libros
Universidad de La Romana > Investigación > Producción Científica Abierto Inglés Objective: This study aims to determine the efficacy of the Acacia arabica (Lam.) Willd. and Cinnamomum camphora (L.) J. Presl. vaginal suppository in addressing heavy menstrual bleeding (HMB) and their impact on participants' health-related quality of life (HRQoL) analyzed using machine learning algorithms. Method: A total of 62 participants were enrolled in a double-dummy, single-center study. They were randomly assigned to either the suppository group (SG), receiving a formulation prepared with Acacia arabica gum (Gond Babul) and camphor from Cinnamomum camphora (Kafoor) through two vaginal suppositories (each weighing 3,500 mg) for 7 days at bedtime along with oral placebo capsules, or the tranexamic group (TG), receiving oral tranexamic acid (500 mg) twice a day for 5 days and two placebo vaginal suppositories during menstruation at bedtime for three consecutive menstrual cycles. The primary outcome was the pictorial blood loss assessment chart (PBLAC) for HMB, and secondary outcomes included hemoglobin level and SF-36 HRQoL questionnaire scores. Additionally, machine learning algorithms such as k-nearest neighbor (KNN), AdaBoost (AB), naive Bayes (NB), and random forest (RF) classifiers were employed for analysis. Results: In the SG and TG, the mean PBLAC score decreased from 635.322 ± 504.23 to 67.70 ± 22.37 and 512.93 ± 283.57 to 97.96 ± 39.25, respectively, at post-intervention (TF3), demonstrating a statistically significant difference (p < 0.001). A higher percentage of participants in the SG achieved normal menstrual blood loss compared to the TG (93.5% vs 74.2%). The SG showed a considerable improvement in total SF-36 scores (73.56%) compared to the TG (65.65%), with a statistically significant difference (p < 0.001). Additionally, no serious adverse events were reported in either group. Notably, machine learning algorithms, particularly AB and KNN, demonstrated the highest accuracy within cross-validation models for both primary and secondary outcomes. Conclusion: The A. arabica and C. camphora vaginal suppository is effective, cost-effective, and safe in controlling HMB. This botanical vaginal suppository provides a novel and innovative alternative to traditional interventions, demonstrating promise as an effective management approach for HMB. metadata Fazmiya, Mohamed Joonus Aynul; Sultana, Arshiya; Heyat, Md Belal Bin; Parveen, Saba; Rahman, Khaleequr; Akhtar, Faijan; Khan, Azmat Ali; Alanazi, Amer M.; Ahmed, Zaheer; Díez, Isabel de la Torre; Brito Ballester, Julién y Saripalli, Tirumala Santhosh Kumar mail SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, julien.brito@uneatlantico.es, SIN ESPECIFICAR (2024) Efficacy of a vaginal suppository formulation prepared with Acacia arabica (Lam.) Willd. gum and Cinnamomum camphora (L.) J. Presl. in heavy menstrual bleeding analyzed using a machine learning technique. Frontiers in Pharmacology, 15. ISSN 1663-9812

Artículo Materias > Biomedicina
Materias > Ingeniería Universidad Europea del Atlántico > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Producción Científica
Universidad Internacional Iberoamericana Puerto Rico > Investigación > Artículos y libros
Universidad Internacional do Cuanza > Investigación > Producción Científica
Universidad de La Romana > Investigación > Producción Científica Abierto Inglés Diabetes is a persistent health condition led by insufficient use or inappropriate use of insulin in the body. If left undetected, it can lead to further complications involving organ damage such as heart, lungs, and eyes. Timely detection of diabetes helps obtain the right medication, diet, and exercise plan to lead a healthy life. ML approach has been utilized to obtain rapid and reliable diabetes detection, however, existing approaches suffer from the use of limited datasets, lack of generalizability, and lower accuracy. This study proposes a novel feature extraction approach to overcome these limitations by using an ensemble of convolutional neural network (CNN) and long short-term memory (LSTM) models. Multiple datasets are combined to make a larger dataset for experiments and multiple features are utilized for investigating the efficacy of the proposed approach. Features from the extra tree classifier, CNN, and LSTM are also considered for comparison. Experimental results reveal the superb performance of CNN-LSTM-based features with random forest model obtaining a 0.99 accuracy score. This performance is further validated by comparison with existing approaches and k-fold cross-validation which shows the proposed approach provides robust results. metadata Rustam, Furqan; Al-Shamayleh, Ahmad Sami; Shafique, Rahman; Aparicio Obregón, Silvia; Calderón Iglesias, Rubén; Gonzalez, J. Pablo Miramontes y Ashraf, Imran mail SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, silvia.aparicio@uneatlantico.es, ruben.calderon@uneatlantico.es, SIN ESPECIFICAR, SIN ESPECIFICAR (2024) Enhanced detection of diabetes mellitus using novel ensemble feature engineering approach and machine learning model. Scientific Reports, 14 (1). ISSN 2045-2322

Artículo Materias > Biomedicina
Materias > Ingeniería Universidad Europea del Atlántico > Investigación > Producción Científica
Fundación Universitaria Internacional de Colombia > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Producción Científica
Universidad Internacional Iberoamericana Puerto Rico > Investigación > Artículos y libros
Universidad Internacional do Cuanza > Investigación > Producción Científica
Universidad de La Romana > Investigación > Producción Científica Abierto Inglés Thyroid illness encompasses a range of disorders affecting the thyroid gland, leading to either hyperthyroidism or hypothyroidism, which can significantly impact metabolism and overall health. Hypothyroidism can cause a slowdown in bodily processes, leading to symptoms such as fatigue, weight gain, depression, and cold sensitivity. Hyperthyroidism can lead to increased metabolism, causing symptoms like rapid weight loss, anxiety, irritability, and heart palpitations. Prompt diagnosis and appropriate treatment are crucial in managing thyroid disorders and improving patients’ quality of life. Thyroid illness affects millions worldwide and can significantly impact their quality of life if left untreated. This research aims to propose an effective artificial intelligence-based approach for the early diagnosis of thyroid illness. An open-access thyroid disease dataset based on 3,772 male and female patient observations is used for this research experiment. This study uses the nominal continuous synthetic minority oversampling technique (SMOTE-NC) for data balancing and a fine-tuned light gradient booster machine (LGBM) technique to diagnose thyroid illness and handle class imbalance problems. The proposed SNL (SMOTE-NC-LGBM) approach outperformed the state-of-the-art approach with high-accuracy performance scores of 0.96. We have also applied advanced machine learning and deep learning methods for comparison to evaluate performance. Hyperparameter optimizations are also conducted to enhance thyroid diagnosis performance. In addition, we have applied the explainable Artificial Intelligence (XAI) mechanism based on Shapley Additive exPlanations (SHAP) to enhance the transparency and interpretability of the proposed method by analyzing the decision-making processes. The proposed research revolutionizes the diagnosis of thyroid disorders efficiently and helps specialties overcome thyroid disorders early. metadata Raza, Ali; Eid, Fatma; Caro Montero, Elisabeth; Delgado Noya, Irene y Ashraf, Imran mail SIN ESPECIFICAR, SIN ESPECIFICAR, elizabeth.caro@uneatlantico.es, irene.delgado@uneatlantico.es, SIN ESPECIFICAR (2024) Enhanced interpretable thyroid disease diagnosis by leveraging synthetic oversampling and machine learning models. BMC Medical Informatics and Decision Making, 24 (1). ISSN 1472-6947

Artículo Materias > Biomedicina
Materias > Alimentación Universidad Europea del Atlántico > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Producción Científica
Universidad Internacional Iberoamericana Puerto Rico > Investigación > Artículos y libros
Universidad Internacional do Cuanza > Investigación > Producción Científica
Universidad de La Romana > Investigación > Producción Científica Abierto Inglés Cardiovascular diseases (CVDs) are one of the main causes of mortality and morbidity worldwide. A healthy diet rich in plant-derived compounds such as (poly)phenols appears to have a key role in improving cardiovascular health. Flavan-3-ols represent a subclass of (poly)phenols of great interest for their possible health benefits. In this review, we summarized the results of clinical studies on vascular outcomes of flavan-3-ol supplementation and we focused on the role of the microbiota in CVD. Clinical trials included in this review showed that supplementation with flavan-3-ols mostly derived from cocoa products significantly reduces blood pressure and improves endothelial function. Studies on catechins from green tea demonstrated better results when involving healthy individuals. From a mechanistic point of view, emerging evidence suggests that microbial metabolites may play a role in the observed effects. Their function extends beyond the previous belief of ROS scavenging activity and encompasses a direct impact on gene expression and protein function. Although flavan-3-ols appear to have effects on cardiovascular health, further studies are needed to clarify and confirm these potential benefits and the rising evidence of the potential involvement of the microbiota. metadata Godos, Justyna; Romano, Giovanni Luca; Laudani, Samuele; Gozzo, Lucia; Guerrera, Ida; Dominguez Azpíroz, Irma; Martínez Díaz, Raquel; Quiles, José L.; Battino, Maurizio; Drago, Filippo; Giampieri, Francesca; Galvano, Fabio y Grosso, Giuseppe mail SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, irma.dominguez@unini.edu.mx, raquel.martinez@uneatlantico.es, jose.quiles@uneatlantico.es, maurizio.battino@uneatlantico.es, SIN ESPECIFICAR, francesca.giampieri@uneatlantico.es, SIN ESPECIFICAR, SIN ESPECIFICAR (2024) Flavan-3-ols and Vascular Health: Clinical Evidence and Mechanisms of Action. Nutrients, 16 (15). p. 2471. ISSN 2072-6643

Artículo Materias > Biomedicina
Materias > Alimentación Universidad Europea del Atlántico > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Producción Científica
Universidad Internacional Iberoamericana Puerto Rico > Investigación > Artículos y libros
Universidad Internacional do Cuanza > Investigación > Producción Científica
Universidad de La Romana > Investigación > Producción Científica Abierto Inglés Isoflavones are a group of (poly)phenols, also defined as phytoestrogens, with chemical structures comparable with estrogen, that exert weak estrogenic effects. These phytochemical compounds have been targeted for their proven antioxidant and protective effects. Recognizing the increasing prevalence of cardiovascular diseases (CVD), there is a growing interest in understanding the potential cardiovascular benefits associated with these phytochemical compounds. Gut microbiota may play a key role in mediating the effects of isoflavones on vascular and endothelial functions, as it is directly implicated in isoflavones metabolism. The findings from randomized clinical trials indicate that isoflavone supplementation may exert putative effects on vascular biomarkers among healthy individuals, but not among patients affected by cardiometabolic disorders. These results might be explained by the enzymatic transformation to which isoflavones are subjected by the gut microbiota, suggesting that a diverse composition of the microbiota may determine the diverse bioavailability of these compounds. Specifically, the conversion of isoflavones in equol—a microbiota-derived metabolite—seems to differ between individuals. Further studies are needed to clarify the intricate molecular mechanisms behind these contrasting results. metadata Laudani, Samuele; Godos, Justyna; Romano, Giovanni Luca; Gozzo, Lucia; Di Domenico, Federica Martina; Dominguez Azpíroz, Irma; Martínez Díaz, Raquel; Giampieri, Francesca; Quiles, José L.; Battino, Maurizio; Drago, Filippo; Galvano, Fabio y Grosso, Giuseppe mail SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, irma.dominguez@unini.edu.mx, raquel.martinez@uneatlantico.es, francesca.giampieri@uneatlantico.es, jose.quiles@uneatlantico.es, maurizio.battino@uneatlantico.es, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR (2024) Isoflavones Effects on Vascular and Endothelial Outcomes: How Is the Gut Microbiota Involved? Pharmaceuticals, 17 (2). p. 236. ISSN 1424-8247

Tesis Materias > Biomedicina Universidad Internacional Iberoamericana Puerto Rico > Investigación > Tesis Doctorales Cerrado Español El intento de acercamiento de tratamientos biológicos, con elevado coste para los ciudadanos, ha impulsado el nacimiento y crecimiento de los medicamentos biosimilares. Moléculas cuya producción está enfocada a ser copias de los principios activos de los medicamentos de origen biológico catalogados como innovadores. Al ser moléculas biológicas, el hecho de ser copias del principio activo se hace complejo, pues pequeñas variaciones en su composición bioquímica pueden afectar a su seguridad y eficacia. A diferencia de los innovadores, cuyo razonamiento de comercialización está dirigido a la seguridad del medicamento mediante estudios clínicos, base para ser comercializado en condiciones seguras, sin embargo, los medicamentos biosimilares, se centran en que sus atributos de calidad sean los más próximos a la molécula que pretenden sustituir. Por ese motivo, mediante el estudio de los atributos críticos de calidad, la farmacología, su comportamiento en un organismo vivo y su composición es posible desarrollar una ecuación que permita facilitar la forma de estudiar la biosimilaridad de una molécula, y mediante una representación gráfica de la misma, se puede facilitar la compresión y graduar el nivel de calidad de un biosimilar. Los atributos que caracterizan a las moléculas son antagonistas o complementarios entre sí, permitiendo establecer un rango de aceptación que permita el desarrollo de un sistema de graduación de la comparabilidad entre innovadores y biosimilares, acercando el concepto hasta la fecha teórico, a un aspecto cuantitativo. Pero siempre tomando en consideración aspectos fundamentales como la incidencia del error del laboratorio en su valoración. Por lo que, basándose en un modelo radial de representación gráfica, resultante del análisis de los diferentes atributos antagonistas y complementarios, y apoyado en una clasificación cuantitativa, las agencias y compañías pueden identificar el tipo de molécula comercializada de forma estandarizada. metadata Lorenzana Suárez, Diego mail diego.lorenzana@doctorado.unib.org (2024) La biosimilaridad de anticuerpos monoclonales frente a sus moléculas de referencia como concepto escalable mediante una ecuación de diseño experimental. Doctoral thesis, SIN ESPECIFICAR.

Artículo Materias > Biomedicina Universidad Europea del Atlántico > Investigación > Producción Científica
Fundación Universitaria Internacional de Colombia > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Producción Científica
Universidad Internacional Iberoamericana Puerto Rico > Investigación > Artículos y libros
Universidad Internacional do Cuanza > Investigación > Producción Científica
Universidad de La Romana > Investigación > Producción Científica Abierto Inglés The evolution of the COVID-19 pandemic has been associated with variations in clinical presentation and severity. Similarly, prediction scores may suffer changes in their diagnostic accuracy. The aim of this study was to test the 30-day mortality predictive validity of the 4C and SEIMC scores during the sixth wave of the pandemic and to compare them with those of validation studies. This was a longitudinal retrospective observational study. COVID-19 patients who were admitted to the Emergency Department of a Spanish hospital from December 15, 2021, to January 31, 2022, were selected. A side-by-side comparison with the pivotal validation studies was subsequently performed. The main measures were 30-day mortality and the 4C and SEIMC scores. A total of 27,614 patients were considered in the study, including 22,361 from the 4C, 4,627 from the SEIMC and 626 from our hospital. The 30-day mortality rate was significantly lower than that reported in the validation studies. The AUCs were 0.931 (95% CI: 0.90–0.95) for 4C and 0.903 (95% CI: 086–0.93) for SEIMC, which were significantly greater than those obtained in the first wave. Despite the changes that have occurred during the coronavirus disease 2019 (COVID-19) pandemic, with a reduction in lethality, scorecard systems are currently still useful tools for detecting patients with poor disease risk, with better prognostic capacity. metadata de Santos Castro, Pedro Ángel; del Pozo Vegas, Carlos; Pinilla Arribas, Leyre Teresa; Zalama Sánchez, Daniel; Sanz-García, Ancor; Vásquez del Águila, Tony Giancarlo; González Izquierdo, Pablo; de Santos Sánchez, Sara; Mazas Pérez-Oleaga, Cristina; Dominguez Azpíroz, Irma; Elío Pascual, Iñaki y Martín-Rodríguez, Francisco mail SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, cristina.mazas@uneatlantico.es, irma.dominguez@unini.edu.mx, inaki.elio@uneatlantico.es, SIN ESPECIFICAR (2024) Performance of the 4C and SEIMC scoring systems in predicting mortality from onset to current COVID-19 pandemic in emergency departments. Scientific Reports, 14 (1). ISSN 2045-2322

Artículo Materias > Biomedicina
Materias > Ingeniería Universidad Europea del Atlántico > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Producción Científica
Universidad Internacional Iberoamericana Puerto Rico > Investigación > Artículos y libros
Universidad Internacional do Cuanza > Investigación > Producción Científica
Universidad de La Romana > Investigación > Producción Científica Cerrado Inglés Leukemia is a type of blood cell cancer that is in the bone marrow’s blood-forming cells. Two types of Leukemia are acute and chronic; acute enhances fast and chronic growth gradually which are further classified into lymphocytic and myeloid leukemias. This work evaluates a unique deep convolutional neural network (CNN) classifier that improves identification precision by carefully examining concatenated peptide patterns. The study uses leukemia protein expression for experiments supporting two different techniques including independence and applied cross-validation. In addition to CNN, multilayer perceptron (MLP), gated recurrent unit (GRU), and recurrent neural network (RNN) are applied. The experimental results show that the CNN model surpasses competitors with its outstanding predictability in independent and cross-validation testing applied on different features extracted from protein expressions such as amino acid composition (AAC) with a group of AAC (GAAC), tripeptide composition (TPC) with a group of TPC (GTPC), and dipeptide composition (DPC) for calculating its accuracies with their receiver operating characteristic (ROC) curve. In independence testing, a feature expression of AAC and a group of GAAC are applied using MLP and CNN modules, and ROC curves are achieved with overall 100% accuracy for the detection of protein patterns. In cross-validation testing, a feature expression on a group of AAC and GAAC patterns achieved 98.33% accuracy which is the highest for the CNN module. Furthermore, ROC curves show a 0.965% extraordinary result for the GRU module. The findings show that the CNN model is excellent at figuring out leukemia illnesses from protein expressions with higher accuracy. metadata Khawaja, Seher Ansar; Farooq, Muhammad Shoaib; Ishaq, Kashif; Alsubaie, Najah; Karamti, Hanen; Caro Montero, Elizabeth; Silva Alvarado, Eduardo René y Ashraf, Imran mail SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, elizabeth.caro@uneatlantico.es, eduardo.silva@funiber.org, SIN ESPECIFICAR (2024) Prediction of leukemia peptides using convolutional neural network and protein compositions. BMC Cancer, 24 (1). ISSN 1471-2407

Artículo Materias > Biomedicina
Materias > Ingeniería Universidad Europea del Atlántico > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Producción Científica
Universidad Internacional Iberoamericana Puerto Rico > Investigación > Artículos y libros
Universidad Internacional do Cuanza > Investigación > Producción Científica
Universidad de La Romana > Investigación > Producción Científica Abierto Inglés Telephysiotherapy has emerged as a vital solution for delivering remote healthcare, particularly in response to global challenges such as the COVID-19 pandemic. This study seeks to enhance telephysiotherapy by developing a system capable of accurately classifying physiotherapeutic exercises using PoseNet, a state-of-the-art pose estimation model. A dataset was collected from 49 participants (35 males, 14 females) performing seven distinct exercises, with twelve anatomical landmarks then extracted using the Google MediaPipe library. Each landmark was represented by four features, which were used for classification. The core challenge addressed in this research involves ensuring accurate and real-time exercise classification across diverse body morphologies and exercise types. Several tree-based classifiers, including Random Forest, Extra Tree Classifier, XGBoost, LightGBM, and Hist Gradient Boosting, were employed. Furthermore, two novel ensemble models called RandomLightHist Fusion and StackedXLightRF are proposed to enhance classification accuracy. The RandomLightHist Fusion model achieved superior accuracy of 99.6%, demonstrating the system’s robustness and effectiveness. This innovation offers a practical solution for providing real-time feedback in telephysiotherapy, with potential to improve patient outcomes through accurate monitoring and assessment of exercise performance. metadata Hussain, Shahzad; Siddiqui, Hafeez Ur Rehman; Saleem, Adil Ali; Raza, Muhammad Amjad; Alemany Iturriaga, Josep; Velarde-Sotres, Álvaro; Díez, Isabel De la Torre y Dudley, Sandra mail SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, josep.alemany@uneatlantico.es, alvaro.velarde@uneatlantico.es, SIN ESPECIFICAR, SIN ESPECIFICAR (2024) Smart Physiotherapy: Advancing Arm-Based Exercise Classification with PoseNet and Ensemble Models. Sensors, 24 (19). p. 6325. ISSN 1424-8220

Artículo Materias > Biomedicina Universidad Europea del Atlántico > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Producción Científica
Universidad Internacional Iberoamericana Puerto Rico > Investigación > Artículos y libros
Universidad de La Romana > Investigación > Producción Científica Abierto Inglés Interleukin-10, a highly effective cytokine recognized for its anti-inflammatory properties, plays a critical role in the immune system. In addition to its well-documented capacity to mitigate inflammation, IL-10 can unexpectedly demonstrate pro-inflammatory characteristics under specific circumstances. The presence of both aspects emphasizes the vital need to identify the IL-10-induced peptide. To mitigate the drawbacks of manual identification, which include its high cost, this study introduces StackIL10, an ensemble learning model based on stacking, to identify IL-10-inducing peptides in a precise and efficient manner. Ten Amino-acid-composition-based Feature Extraction approaches are considered. The StackIL10, stacking ensemble, the model with five optimized Machine Learning Algorithm (specifically LGBM, RF, SVM, Decision Tree, KNN) as the base learners and a Logistic Regression as the meta learner was constructed, and the identification rate reached 91.7%, MCC of 0.833 with 0.9078 Specificity. Experiments were conducted to examine the impact of various enhancement techniques on the correctness of IL-10 Prediction. These experiments included comparisons between single models and various combinations of stacking-based ensemble models. It was demonstrated that the model proposed in this study was more effective than singular models and produced satisfactory results, thereby improving the identification of peptides that induce IL-10. metadata Usmani, Salman Sadullah; Tuhin, Izaz Ahmmed; Mia, Md. Rajib; Islam, Md. Monirul; Mahmud, Imran; Uc Ríos, Carlos Eduardo; Fabian Gongora, Henry; Ashraf, Imran y Samad, Md. Abdus mail SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, carlos.uc@unini.edu.mx, henry.gongora@uneatlantico.es, SIN ESPECIFICAR, SIN ESPECIFICAR (2024) StackIL10: A stacking ensemble model for the improved prediction of IL-10 inducing peptides. PLOS ONE, 19 (11). e0313835. ISSN 1932-6203

2023

Artículo Materias > Biomedicina
Materias > Ingeniería Universidad Europea del Atlántico > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Producción Científica
Universidad Internacional Iberoamericana Puerto Rico > Investigación > Artículos y libros
Universidad Internacional do Cuanza > Investigación > Producción Científica Abierto Inglés In the last decade, artificial intelligence (AI) and AI-mediated technologies have undergone rapid evolution in healthcare and medicine, from apps to computer software able to analyze medical images, robotic surgery and advanced data storage system. The main aim of the present commentary is to briefly describe the evolution of AI and its applications in healthcare, particularly in nutrition and clinical biochemistry. Indeed, AI is revealing itself to be an important tool in clinical nutrition by using telematic means to self-monitor various health metrics, including blood glucose levels, body weight, heart rate, fat percentage, blood pressure, activity tracking and calorie intake trackers. In particular, the application of the most common digital technologies used in the field of nutrition as well as the employment of AI in the management of diabetes and obesity, two of the most common nutrition-related pathologies worldwide, will be presented. metadata Salinari, Alessia; Machì, Michele; Armas Diaz, Yasmany; Cianciosi, Danila; Qi, Zexiu; Yang, Bei; Ferreiro Cotorruelo, Maria Soledad; Gracia Villar, Santos; Dzul López, Luis Alonso; Battino, Maurizio y Giampieri, Francesca mail SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, santos.gracia@uneatlantico.es, luis.dzul@uneatlantico.es, maurizio.battino@uneatlantico.es, francesca.giampieri@uneatlantico.es (2023) The Application of Digital Technologies and Artificial Intelligence in Healthcare: An Overview on Nutrition Assessment. Diseases, 11 (3). p. 97. ISSN 2079-9721

Artículo Materias > Biomedicina Universidad Internacional Iberoamericana Puerto Rico > Investigación > Artículos y libros Abierto Inglés Background The negative effects of COVID-19 infections during pregnancy have been amply described, however, the persistent sequels of this infection have not been explored so far. Objective The aim of this study was to describe persisting symptoms after COVID-19 infection in pregnant and non-pregnant women in Ecuador. Methods A cross-sectional analysis based on an online, self-reporting questionnaire was conducted in Ecuador from April to July 2022. Participants were invited by social media, radio, and TV to voluntarily participate in our study. A total of 457 surveys were included in this study. We compared risk factor variables and long-term persisting symptoms of pregnant and non-pregnant women in Ecuador. Results Overall, 247 (54.1 %) responders claimed to have long-term symptoms after SARS-CoV-2 infection. Most of these symptoms were reported by non-pregnant women (94.0 %). The most common Long-COVID symptoms in pregnant women were fatigue (10.6 %), hair loss (9.6 %), and difficulty concentrating (6.2 %). We found that pregnant women who smoked had a higher risk of suffering fatigue. Conclusions The most frequent Long-COVID symptoms in pregnant women were fatigue, hair loss, and difficulty concentrating. Apparently, the patterns of presentation of long-term sequelae of SARS-CoV-2 infection in pregnant women do not differ significantly from reports available from studies in the general population. metadata Vásconez-González, Jorge; Fernandez-Naranjo, Raul; Izquierdo Condoy, Juan Sebastian; Delgado-Moreira, Karen; Cordovez, Simone; Tello-De-la-Torre, Andrea; Paz, Clara; Castillo, Diana; Izquierdo-Condoy, Nathaly; Carrington, Sarah J. y Ortiz-Prado, Esteban mail SIN ESPECIFICAR (2023) Comparative analysis of long-term self-reported COVID-19 symptoms among pregnant women. Journal of Infection and Public Health, 16 (3). pp. 430-440. ISSN 18760341

Artículo Materias > Biomedicina
Materias > Ingeniería Universidad Europea del Atlántico > Investigación > Producción Científica
Fundación Universitaria Internacional de Colombia > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Producción Científica
Universidad Internacional Iberoamericana Puerto Rico > Investigación > Artículos y libros
Universidad Internacional do Cuanza > Investigación > Producción Científica Abierto Inglés Artificial intelligence has made substantial progress in medicine. Automated dental imaging interpretation is one of the most prolific areas of research using AI. X-ray and infrared imaging systems have enabled dental clinicians to identify dental diseases since the 1950s. However, the manual process of dental disease assessment is tedious and error-prone when diagnosed by inexperienced dentists. Thus, researchers have employed different advanced computer vision techniques, and machine- and deep-learning models for dental disease diagnoses using X-ray and near-infrared imagery. Despite the notable development of AI in dentistry, certain factors affect the performance of the proposed approaches, including limited data availability, imbalanced classes, and lack of transparency and interpretability. Hence, it is of utmost importance for the research community to formulate suitable approaches, considering the existing challenges and leveraging findings from the existing studies. Based on an extensive literature review, this survey provides a brief overview of X-ray and near-infrared imaging systems. Additionally, a comprehensive insight into challenges faced by researchers in the dental domain has been brought forth in this survey. The article further offers an amalgamative assessment of both performances and methods evaluated on public benchmarks and concludes with ethical considerations and future research avenues. metadata Shafi, Imran; Fatima, Anum; Afzal, Hammad; Díez, Isabel de la Torre; Lipari, Vivian; Breñosa, Jose y Ashraf, Imran mail SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, vivian.lipari@uneatlantico.es, josemanuel.brenosa@uneatlantico.es, SIN ESPECIFICAR (2023) A Comprehensive Review of Recent Advances in Artificial Intelligence for Dentistry E-Health. Diagnostics, 13 (13). p. 2196. ISSN 2075-4418

Artículo Materias > Biomedicina
Materias > Ingeniería Universidad Europea del Atlántico > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Producción Científica
Universidad Internacional Iberoamericana Puerto Rico > Investigación > Artículos y libros
Universidad Internacional do Cuanza > Investigación > Producción Científica Abierto Inglés A novel approach is presented in this study for the classification of lower limb disorders, with a specific emphasis on the knee, hip, and ankle. The research employs gait analysis and the extraction of PoseNet features from video data in order to effectively identify and categorize these disorders. The PoseNet algorithm facilitates the extraction of key body joint movements and positions from videos in a non-invasive and user-friendly manner, thereby offering a comprehensive representation of lower limb movements. The features that are extracted are subsequently standardized and employed as inputs for a range of machine learning algorithms, such as Random Forest, Extra Tree Classifier, Multilayer Perceptron, Artificial Neural Networks, and Convolutional Neural Networks. The models undergo training and testing processes using a dataset consisting of 174 real patients and normal individuals collected at the Tehsil Headquarter Hospital Sadiq Abad. The evaluation of their performance is conducted through the utilization of K-fold cross-validation. The findings exhibit a notable level of accuracy and precision in the classification of various lower limb disorders. Notably, the Artificial Neural Networks model achieves the highest accuracy rate of 98.84%. The proposed methodology exhibits potential in enhancing the diagnosis and treatment planning of lower limb disorders. It presents a non-invasive and efficient method of analyzing gait patterns and identifying particular conditions. metadata Siddiqui, Hafeez Ur Rehman; Saleem, Adil Ali; Raza, Muhammad Amjad; Gracia Villar, Santos; Dzul Lopez, Luis; Diez, Isabel de la Torre; Rustam, Furqan y Dudley, Sandra mail SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, santos.gracia@uneatlantico.es, luis.dzul@unini.edu.mx, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR (2023) Empowering Lower Limb Disorder Identification through PoseNet and Artificial Intelligence. Diagnostics, 13 (18). p. 2881. ISSN 2075-4418

Artículo Materias > Biomedicina Universidad Europea del Atlántico > Investigación > Producción Científica
Fundación Universitaria Internacional de Colombia > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Producción Científica
Universidad Internacional Iberoamericana Puerto Rico > Investigación > Artículos y libros
Universidad Internacional do Cuanza > Investigación > Producción Científica Abierto Inglés Background and Aims The 2022-mpox outbreak has spread worldwide in a short time. Integrated knowledge of the epidemiology, clinical characteristics, and transmission of mpox are limited. This systematic review of peer-reviewed articles and gray literature was conducted to shed light on the epidemiology, clinical features, and transmission of 2022-mpox outbreak. Methods We identified 45 peer-reviewed manuscripts for data analysis. The standards of the Preferred Reporting Items for Systematic Review and Meta-Analysis (PRISMA) Statement and Cochrane Collaboration were followed for conducting the study. Results The case number of mpox has increased about 100 times worldwide. About 99% of the cases in 2022 outbreak was from non-endemic regions. Men (70%–98% cases) were mostly infected with homosexual and bisexual behavior (30%–60%). The ages of the infected people ranged between 30 and 40 years. The presence of HIV and sexually transmitted infections among 30%–60% of cases were reported. Human-to-human transmission via direct contact and different body fluids were involved in the majority of the cases (90%–100%). Lesions in genitals, perianal, and anogenital areas were more prevalent. Unusually, pharyngitis (15%–40%) and proctitis (20%–40%) were more common during 2022 outbreak than pre-2022 outbreaks. Brincidofovir is approved for the treatment of smallpox by FDA (USA). Two vaccines, including JYNNEOSTM and ACAM2000®, are approved and used for pre- and post-prophylaxis in cases. About 100% of the cases in non-endemic regions were associated with isolates of IIb clade with a divergence of 0.0018–0.0035. Isolates from B.1 lineage were the most predominant followed by B.1.2 and B.1.10. Conclusion This study will add integrated knowledge of the epidemiology, clinical features, and transmission of mpox. metadata Sharif, Nadim; Sharif, Nazmul; Alzahrani, Khalid J.; Halawani, Ibrahim F.; Alzahrani, Fuad M.; Díez, Isabel De la Torre; Lipari, Vivian; López Flores, Miguel Ángel; Parvez, Anowar K. y Dey, Shuvra K. mail SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, vivian.lipari@uneatlantico.es, miguelangel.lopez@uneatlantico.es, SIN ESPECIFICAR, SIN ESPECIFICAR (2023) Molecular epidemiology, transmission and clinical features of 2022‐mpox outbreak: A systematic review. Health Science Reports, 6 (10). ISSN 2398-8835

Artículo Materias > Biomedicina Universidad Europea del Atlántico > Investigación > Producción Científica
Fundación Universitaria Internacional de Colombia > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Producción Científica
Universidad Internacional Iberoamericana Puerto Rico > Investigación > Artículos y libros
Universidad Internacional do Cuanza > Investigación > Producción Científica
Universidad de La Romana > Investigación > Producción Científica Abierto Inglés Objective The aim was to explore the association of demographic and prehospital parameters with short-term and long-term mortality in acute life-threatening cardiovascular disease by using a hazard model, focusing on elderly individuals, by comparing patients under 75 years versus patients over 75 years of age. Design Prospective, multicentre, observational study. Setting Emergency medical services (EMS) delivery study gathering data from two back-to-back studies between 1 October 2019 and 30 November 2021. Six advanced life support (ALS), 43 basic life support and five hospitals in Spain were considered. Participants Adult patients suffering from acute life-threatening cardiovascular disease attended by the EMS. Primary and secondary outcome measures The primary outcome was in-hospital mortality from any cause within the first to the 365 days following EMS attendance. The main measures included prehospital demographics, biochemical variables, prehospital ALS techniques used and syndromic suspected conditions. Results A total of 1744 patients fulfilled the inclusion criteria. The 365-day cumulative mortality in the elderly amounted to 26.1% (229 cases) versus 11.6% (11.6%) in patients under 75 years old. Elderly patients (≥75 years) presented a twofold risk of mortality compared with patients ≤74 years. Life-threatening interventions (mechanical ventilation, cardioversion and defibrillation) were also related to a twofold increased risk of mortality. Importantly, patients suffering from acute heart failure presented a more than twofold increased risk of mortality. Conclusions This study revealed the prehospital variables associated with the long-term mortality of patients suffering from acute cardiovascular disease. Our results provide important insights for the development of specific codes or scores for cardiovascular diseases to facilitate the risk of mortality characterisation. metadata del Pozo Vegas, Carlos; Zalama-Sánchez, Daniel; Sanz-Garcia, Ancor; López-Izquierdo, Raúl; Sáez-Belloso, Silvia; Mazas Pérez-Oleaga, Cristina; Dominguez Azpíroz, Irma; Elío Pascual, Iñaki y Martín-Rodríguez, Francisco mail SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, cristina.mazas@uneatlantico.es, irma.dominguez@unini.edu.mx, inaki.elio@uneatlantico.es, SIN ESPECIFICAR (2023) Prehospital acute life-threatening cardiovascular disease in elderly: an observational, prospective, multicentre, ambulance-based cohort study. BMJ Open, 13 (11). e078815. ISSN 2044-6055

Artículo Materias > Biomedicina Universidad Europea del Atlántico > Investigación > Producción Científica
Fundación Universitaria Internacional de Colombia > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Producción Científica
Universidad Internacional Iberoamericana Puerto Rico > Investigación > Artículos y libros
Universidad Internacional do Cuanza > Investigación > Producción Científica Abierto Inglés Background: Nowadays, there is no gold standard score for prehospital sepsis and sepsis-related mortality identification. The aim of the present study was to analyze the performance of qSOFA, NEWS2 and mSOFA as sepsis predictors in patients with infection-suspected in prehospital care. The second objective is to study the predictive ability of the aforementioned scores in septic-shock and in-hospital mortality. Methods: Prospective, ambulance-based, and multicenter cohort study, developed by the emergency medical services, among patients (n = 535) with suspected infection transferred by ambulance with high-priority to the emergency department (ED). The study enrolled 40 ambulances and 4 ED in Spain between 1 January 2020, and 30 September 2021. All the variables used in the scores, in addition to socio-demographic data, standard vital signs, prehospital analytical parameters (glucose, lactate, and creatinine) were collected. For the evaluation of the scores, the discriminative power, calibration curve and decision curve analysis (DCA) were used. Results: The mSOFA outperformed the other two scores for mortality, presenting the following AUCs: 0.877 (95%CI 0.841–0.913), 0.761 (95%CI 0.706–0.816), 0.731 (95%CI 0.674–0.788), for mSOFA, NEWS, and qSOFA, respectively. No differences were found for sepsis nor septic shock, but mSOFA’s AUCs was higher than the one of the other two scores. The calibration curve and DCA presented similar results. Conclusion: The use of mSOFA could provide and extra insight regarding the short-term mortality and sepsis diagnostic, backing its recommendation in the prehospital scenario. metadata Melero-Guijarro, Laura; Sanz-García, Ancor; Martín-Rodríguez, Francisco; Lipari, Vivian; Mazas Pérez-Oleaga, Cristina; Carvajal-Altamiranda, Stefanía; Martínez López, Nohora Milena; Dominguez Azpíroz, Irma; Castro Villamor, Miguel A.; Sánchez Soberón, Irene y López-Izquierdo, Raúl mail SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, vivian.lipari@uneatlantico.es, cristina.mazas@uneatlantico.es, stefania.carvajal@uneatlantico.es, nohora.martinez@uneatlantico.es, irma.dominguez@unini.edu.mx, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR (2023) Prehospital qSOFA, mSOFA, and NEWS2 performance for sepsis prediction: A prospective, multi-center, cohort study. Frontiers in Medicine, 10. ISSN 2296-858X

Artículo Materias > Biomedicina Universidad Europea del Atlántico > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Producción Científica
Universidad Internacional Iberoamericana Puerto Rico > Investigación > Artículos y libros
Universidad Internacional do Cuanza > Investigación > Producción Científica
Universidad de La Romana > Investigación > Producción Científica Abierto Inglés Introduction: Rotavirus infection is a major cause of mortality among children under 5 years in Bangladesh. There is lack of integrated studies on rotavirus prevalence and genetic diversity during 1973 to 2023 in Bangladesh. Methods: This meta-analysis was conducted to determine the prevalence, genotypic diversity and seasonal distribution of rotavirus during pre-vaccination period in Bangladesh. This study included published articles on rotavirus A, rotavirus B and rotavirus C. We used Medline, Scopus and Google Scholar for published articles. Selected literatures were published between 1973 to 2023. Results: This study detected 12431 research articles published on rotavirus. Based on the inclusion criteria, 29 of 75 (30.2%) studies were selected. Molecular epidemiological data was taken from 29 articles, prevalence data from 29 articles, and clinical symptoms from 19 articles. The pooled prevalence of rotavirus was 30.1% (95% CI: 22%-45%, p = 0.005). Rotavirus G1 (27.1%, 2228 of 8219) was the most prevalent followed by G2 (21.09%, 1733 of 8219), G4 (11.58%, 952 of 8219), G9 (9.37%, 770 of 8219), G12 (8.48%, 697 of 8219), and G3 (2.79%, 229 of 8219), respectively. Genotype P[8] (40.6%, 2548 of 6274) was the most prevalent followed by P[4] (12.4%, 777 of 6274) and P[6] (6.4%, 400 of 6274), respectively. Rotavirus G1P[8] (19%) was the most frequent followed by G2P [4] (9.4%), G12P[8] (7.2%), and G9P[8], respectively. Rotavirus infection had higher odds of occurrence during December and February (aOR: 2.86, 95% CI: 2.43-3.6, p = 0.001). Discussion: This is the first meta-analysis including all the studies on prevalence, molecular epidemiology, and genetic diversity of rotavirus from 1973 to 2023, pre-vaccination period in Bangladesh. This study will provide overall scenario of rotavirus genetic diversity and seasonality during pre-vaccination period and aids in policy making for rotavirus vaccination program in Bangladesh. This work will add valuable knowledge for vaccination against rotavirus and compare the data after starting vaccination in Bangladesh. metadata Sharif, Nadim; Sharif, Nazmul; Khan, Afsana; Dominguez Azpíroz, Irma; Martínez Díaz, Raquel; Díez, Isabel De la Torre; Parvez, Anowar Khasru y Dey, Shuvra Kanti mail SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, irma.dominguez@unini.edu.mx, raquel.martinez@uneatlantico.es, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR (2023) Prevalence and genetic diversity of rotavirus in Bangladesh during pre-vaccination period, 1973-2023: a meta-analysis. Frontiers in Immunology, 14. ISSN 1664-3224

Artículo Materias > Biomedicina Universidad Europea del Atlántico > Investigación > Producción Científica
Fundación Universitaria Internacional de Colombia > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Producción Científica
Universidad Internacional Iberoamericana Puerto Rico > Investigación > Artículos y libros
Universidad Internacional do Cuanza > Investigación > Producción Científica Abierto Inglés Introduction: Co-prevalence of long-COVID-19, cardiovascular diseases and diabetes is one of the major health challenges of the pandemic worldwide. Studies on long-COVID-19 and associated health outcomes are absent in Bangladesh. The main aim of this study was to determine the prevalence and impact of long-COVID-19 on preexisting diabetes and cardiovascular diseases (CVD) on health outcomes among patients in Bangladesh. Methods: We collected data from 3,250 participants in Bangladesh, retrospectively. Multivariable logistic regression model was used to determine the odds ratio between independent and dependent variables. Kaplan-Meier survival curve was used to determine the cumulative survival. Results: COVID-19 was detected among 73.4% (2,385 of 3,250) participants. Acute long-COVID-19 was detected among 28.4% (678 of 2,385) and chronic long-COVID-19 among 71.6% (1,707 of 2,385) patients. CVD and diabetes were found among 32%, and 24% patients, respectively. Mortality rate was 18% (585 of 3,250) among the participants. Co-prevalence of CVD, diabetes and COVID-19 was involved in majority of fatality (95%). Fever (97%), dry cough (87%) and loss of taste and smell (85%) were the most prevalent symptoms. Patients with co-prevalence of CVD, diabetes and COVID-19 had higher risk of fatality (OR: 3.65, 95% CI, 2.79–4.24). Co-prevalence of CVD, diabetes and chronic long-COVID-19 were detected among 11.9% patients. Discussion: Risk of hospitalization and fatality reduced significantly among the vaccinated. This is one of the early studies on long-COVID-19 in Bangladesh. metadata Sharif, Nadim; Sharif, Nazmul; Khan, Afsana; Halawani, Ibrahim F.; Alzahrani, Fuad M.; Alzahrani, Khalid J.; Díez, Isabel De la Torre; Ramírez-Vargas, Debora L.; Kuc Castilla, Ángel Gabriel; Parvez, Anowar Khasru y Dey, Shuvra Kanti mail SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, debora.ramirez@unini.edu.mx, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR (2023) Prevalence and impact of long COVID-19 among patients with diabetes and cardiovascular diseases in Bangladesh. Frontiers in Public Health, 11. ISSN 2296-2565

Artículo Materias > Biomedicina Universidad Europea del Atlántico > Investigación > Producción Científica
Fundación Universitaria Internacional de Colombia > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Producción Científica
Universidad Internacional Iberoamericana Puerto Rico > Investigación > Artículos y libros
Universidad Internacional do Cuanza > Investigación > Producción Científica Abierto Inglés Mutations allow viruses to continuously evolve by changing their genetic code to adapt to the hosts they infect. It is an adaptive and evolutionary mechanism that helps viruses acquire characteristics favoring their survival and propagation. The COVID-19 pandemic declared by the WHO in March 2020 is caused by the SARS-CoV-2 virus. The non-stop adaptive mutations of this virus and the emergence of several variants over time with characteristics favoring their spread constitute one of the biggest obstacles that researchers face in controlling this pandemic. Understanding the mutation mechanism allows for the adoption of anticipatory measures and the proposal of strategies to control its propagation. In this study, we focus on the mutations of this virus, and we propose the SARSMutOnto ontology to model SARS-CoV-2 mutations reported by Pango researchers. A detailed description is given for each mutation. The genes where the mutations occur and the genomic structure of this virus are also included. The sub-lineages and the recombinant sub-lineages resulting from these mutations are additionally represented while maintaining their hierarchy. We developed a Python-based tool to automatically generate this ontology from various published Pango source files. At the end of this paper, we provide some examples of SPARQL queries that can be used to exploit this ontology. SARSMutOnto might become a ‘wet bench’ machine learning tool for predicting likely future mutations based on previous mutations. metadata Bakkas, Jamal; Hanine, Mohamed; Chekry, Abderrahman; Gounane, Said; de la Torre Díez, Isabel; Lipari, Vivian; Martínez López, Nohora Milena y Ashraf, Imran mail SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, vivian.lipari@uneatlantico.es, nohora.martinez@uneatlantico.es, SIN ESPECIFICAR (2023) SARSMutOnto: An Ontology for SARS-CoV-2 Lineages and Mutations. Viruses, 15 (2). p. 505. ISSN 1999-4915

Artículo Materias > Biomedicina
Materias > Ingeniería
Materias > Alimentación Universidad Europea del Atlántico > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Producción Científica
Universidad Internacional Iberoamericana Puerto Rico > Investigación > Artículos y libros
Universidad Internacional do Cuanza > Investigación > Producción Científica Cerrado Inglés Obesity and overweight has increased in the last year and has become a pandemic disease, the result of sedentary lifestyles and unhealthy diets rich in sugars, refined starches, fats and calories. Machine learning (ML) has proven to be very useful in the scientific community, especially in the health sector. With the aim of providing useful tools to help nutritionists and dieticians, research focused on the development of ML and Deep Learning (DL) algorithms and models is searched in the literature. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) protocol has been used, a very common technique applied to carry out revisions. In our proposal, 17 articles have been filtered in which ML and DL are applied in the prediction of diseases, in the delineation of treatment strategies, in the improvement of personalized nutrition and more. Despite expecting better results with the use of DL, according to the selected investigations, the traditional methods are still the most used and the yields in both cases fluctuate around positive values, conditioned by the databases (transformed in each case) to a greater extent than by the artificial intelligence paradigm used. Conclusions: An important compilation is provided for the literature in this area. ML models are time-consuming to clean data, but (like DL) they allow automatic modeling of large volumes of data which makes them superior to traditional statistics. metadata Ferreras, Antonio; Sumalla Cano, Sandra; Martínez-Licort, Rosmeri; Elío Pascual, Iñaki; Tutusaus, Kilian; Prola, Thomas; Vidal Mazón, Juan Luis; Sahelices, Benjamín y de la Torre Díez, Isabel mail SIN ESPECIFICAR, sandra.sumalla@uneatlantico.es, SIN ESPECIFICAR, inaki.elio@uneatlantico.es, kilian.tutusaus@uneatlantico.es, thomas.prola@uneatlantico.es, juanluis.vidal@uneatlantico.es, SIN ESPECIFICAR, SIN ESPECIFICAR (2023) Systematic Review of Machine Learning applied to the Prediction of Obesity and Overweight. Journal of Medical Systems, 47 (1). ISSN 1573-689X

Artículo Materias > Biomedicina
Materias > Ingeniería Universidad Europea del Atlántico > Investigación > Producción Científica
Fundación Universitaria Internacional de Colombia > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Producción Científica
Universidad Internacional Iberoamericana Puerto Rico > Investigación > Artículos y libros
Universidad Internacional do Cuanza > Investigación > Producción Científica Abierto Inglés This study sought to investigate how different brain regions are affected by Alzheimer’s disease (AD) at various phases of the disease, using independent component analysis (ICA). The study examines six regions in the mild cognitive impairment (MCI) stage, four in the early stage of Alzheimer’s disease (AD), six in the moderate stage, and six in the severe stage. The precuneus, cuneus, middle frontal gyri, calcarine cortex, superior medial frontal gyri, and superior frontal gyri were the areas impacted at all phases. A general linear model (GLM) is used to extract the voxels of the previously mentioned regions. The resting fMRI data for 18 AD patients who had advanced from MCI to stage 3 of the disease were obtained from the ADNI public source database. The subjects include eight women and ten men. The voxel dataset is used to train and test ten machine learning algorithms to categorize the MCI, mild, moderate, and severe stages of Alzheimer’s disease. The accuracy, recall, precision, and F1 score were used as conventional scoring measures to evaluate the classification outcomes. AdaBoost fared better than the other algorithms and obtained a phenomenal accuracy of 98.61%, precision of 99.00%, and recall and F1 scores of 98.00% each. metadata Shahzadi, Samra; Butt, Naveed Anwer; Sana, Muhammad Usman; Elío Pascual, Iñaki; Briones Urbano, Mercedes; Díez, Isabel de la Torre y Ashraf, Imran mail SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, inaki.elio@uneatlantico.es, mercedes.briones@uneatlantico.es, SIN ESPECIFICAR, SIN ESPECIFICAR (2023) Voxel Extraction and Multiclass Classification of Identified Brain Regions across Various Stages of Alzheimer’s Disease Using Machine Learning Approaches. Diagnostics, 13 (18). p. 2871. ISSN 2075-4418

Artículo Materias > Biomedicina
Materias > Ingeniería Universidad Europea del Atlántico > Investigación > Producción Científica
Fundación Universitaria Internacional de Colombia > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Producción Científica
Universidad Internacional Iberoamericana Puerto Rico > Investigación > Artículos y libros
Universidad Internacional do Cuanza > Investigación > Producción Científica Abierto Inglés Objective This study aims to develop a lightweight convolutional neural network-based edge federated learning architecture for COVID-19 detection using X-ray images, aiming to minimize computational cost, latency, and bandwidth requirements while preserving patient privacy. Method The proposed method uses an edge federated learning architecture to optimize task allocation and execution. Unlike in traditional edge networks where requests from fixed nodes are handled by nearby edge devices or remote clouds, the proposed model uses an intelligent broker within the federation to assess member edge cloudlets' parameters, such as resources and hop count, to make optimal decisions for task offloading. This approach enhances performance and privacy by placing tasks in closer proximity to the user. DenseNet is used for model training, with a depth of 60 and 357,482 parameters. This resource-aware distributed approach optimizes computing resource utilization within the edge-federated learning architecture. Results The experimental results demonstrate significant improvements in various performance metrics. The proposed method reduces training time by 53.1%, optimizes CPU and memory utilization by 17.5% and 33.6%, and maintains accurate COVID-19 detection capabilities without compromising the F1 score, demonstrating the efficiency and effectiveness of the lightweight convolutional neural network-based edge federated learning architecture. Conclusion Existing studies predominantly concentrate on either privacy and accuracy or load balancing and energy optimization, with limited emphasis on training time. The proposed approach offers a comprehensive performance-centric solution that simultaneously addresses privacy, load balancing, and energy optimization while reducing training time, providing a more holistic and balanced solution for optimal system performance. metadata Alvi, Sohaib Bin Khalid; Nayyer, Muhammad Ziad; Jamal, Muhammad Hasan; Raza, Imran; de la Torre Diez, Isabel; Rodríguez Velasco, Carmen Lilí; Breñosa, Jose y Ashraf, Imran mail SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, carmen.rodriguez@uneatlantico.es, josemanuel.brenosa@uneatlantico.es, SIN ESPECIFICAR (2023) A lightweight deep learning approach for COVID-19 detection using X-ray images with edge federation. DIGITAL HEALTH, 9. ISSN 2055-2076

2022

Tesis Materias > Biomedicina
Materias > Educación Universidad Europea del Atlántico > Docencia > Trabajos finales de Máster
Universidad Internacional Iberoamericana México > Docencia > Trabajos finales de Máster
Universidad Internacional Iberoamericana Puerto Rico > Docencia > Trabajos finales de Máster Cerrado Español El ecosistema en todo el mundo facilita recursos básicos para sobrevivir. El Futuro depende de la diversidad biológica: los animales, plantas, bosques, mares, y demás ecología del mundo. De ellas suplimos nuestras necesidades primordiales como los alimentos, fármacos, agua, etc.En los últimos tiempos el gran desarrollo en el turismo ha aumentado a gran escala, perjudicando las áreas protegidas. En la Republica Dominicana el turismo representa una gran importancia para el país, considerando el turismo sostenible o ecoturismo. En este sentido, el proyecto que se presentara a continuación examina las zonas protegidas del país, tratando de llegar a análisis con referencia a las particularidades del publico que visita estas áreas. Nuestro objetivo general es a través de la investigación conocer la situación actualizada del ecoturismo, mediante revisión de documentos y actividades de la zona para poder analizar el movimiento ecoturístico de Punta Cana.En nuestros objetivos específicos es determinar si el conocimiento del medio ambiente y las actividades hacia el ecoturismo son variables conceptuales apropiadas para medir las percepciones de los ecoturistas en las áreas protegidas, analizar si los servicios de los recursos son variables conceptuales apropiadas para medir las satisfacciones de los ecoturistas en las áreas protegidas y evaluar la consistencia interna y la validez de instrumento de medida para el valor hacia los recursos ecoturísticos. metadata Mota Silvestre, Kary Andiana mail Kary.mota@me.com (2022) Análisis del Ecoturismo en Punta Cana, Republica Dominicana. Masters thesis, SIN ESPECIFICAR.

Artículo Materias > Biomedicina
Materias > Ingeniería Universidad Europea del Atlántico > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Producción Científica
Universidad Internacional Iberoamericana Puerto Rico > Investigación > Artículos y libros
Universidad Internacional do Cuanza > Investigación > Producción Científica Abierto Inglés Asthma is a deadly disease that affects the lungs and air supply of the human body. Coronavirus and its variants also affect the airways of the lungs. Asthma patients approach hospitals mostly in a critical condition and require emergency treatment, which creates a burden on health institutions during pandemics. The similar symptoms of asthma and coronavirus create confusion for health workers during patient handling and treatment of disease. The unavailability of patient history to physicians causes complications in proper diagnostics and treatments. Many asthma patient deaths have been reported especially during pandemics, which necessitates an efficient framework for asthma patients. In this article, we have proposed a blockchain consortium healthcare framework for asthma patients. The proposed framework helps in managing asthma healthcare units, coronavirus patient records and vaccination centers, insurance companies, and government agencies, which are connected through the secure blockchain network. The proposed framework increases data security and scalability as it stores encrypted patient data on the Interplanetary File System (IPFS) and keeps data hash values on the blockchain. The patient data are traceable and accessible to physicians and stakeholders, which helps in accurate diagnostics, timely treatment, and the management of patients. The smart contract ensures the execution of all business rules. The patient profile generation mechanism is also discussed. The experiment results revealed that the proposed framework has better transaction throughput, query delay, and security than existing solutions metadata Farooq, Muhammad Shoaib; Suhail, Maryam; Qureshi, Junaid Nasir; Rustam, Furqan; de la Torre Díez, Isabel; Vidal Mazón, Juan Luis; Rodríguez Velasco, Carmen Lilí y Ashraf, Imran mail SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, juanluis.vidal@uneatlantico.es, carmen.rodriguez@uneatlantico.es, SIN ESPECIFICAR (2022) Consortium Framework Using Blockchain for Asthma Healthcare in Pandemics. Sensors, 22 (21). p. 8582. ISSN 1424-8220

Artículo Materias > Biomedicina
Materias > Ingeniería Universidad Europea del Atlántico > Investigación > Producción Científica
Fundación Universitaria Internacional de Colombia > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Producción Científica
Universidad Internacional Iberoamericana Puerto Rico > Investigación > Artículos y libros
Universidad Internacional do Cuanza > Investigación > Producción Científica Abierto Español Patient care and convenience remain the concern of medical professionals and caregivers alike. An unconscious patient confined to a bed may develop fluid accumulation and pressure sores due to inactivity and deficiency of oxygen flow. Moreover, weight monitoring is crucial for an effective treatment plan, which is difficult to measure for bedridden patients. This paper presents the design and development of a smart and cost-effective independent system for lateral rotation, movement, weight measurement, and transporting immobile patients. Optimal dimensions and practical design specifications are determined by a survey across various hospitals. Subsequently, the proposed hoist-based weighing and turning mechanism is CAD-modeled and simulated. Later, the structural analysis is carried out to select suitable metallurgy for various sub-assemblies to ensure design reliability. After fabrication, optimization, integration, and testing procedures, the base frame is designed to mount a hydraulic motor for the actuator, a DC power source for self-sustenance, and lockable wheels for portability. The installation of a weighing scale and a hydraulic actuator is ensured to lift the patient for weight measuring up to 600 pounds or lateral turning of 80 degrees both ways. The developed system offers simple operating characteristics, allows for keeping patient weight records, and assists nurses in changing patients’ lateral positions both ways, comfortably massage patients’ backs, and transport them from one bed to another. Additionally, being lightweight offers reduced contact with the patient to increase the healthcare staff’s safety in pandemics; it is also height adjustable and portable, allowing for use with multiple-sized beds and easy transportation across the medical facility. The feedback from paramedics is encouraging regarding reducing labor-intensive nursing tasks, alleviating the discomfort of long-term bed-ridden patients, and allowing medical practitioners to suggest better treatment plans metadata Shafi, Imran; Farooq, Muhammad Siddique; De La Torre Díez, Isabel; Breñosa, Jose; Martínez Espinosa, Julio César y Ashraf, Imran mail SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, josemanuel.brenosa@uneatlantico.es, ulio.martinez@unini.edu.mx, SIN ESPECIFICAR (2022) Design and Development of Smart Weight Measurement, Lateral Turning and Transfer Bedding for Unconscious Patients in Pandemics. Healthcare, 10 (11). p. 2174. ISSN 2227-9032

Tesis Materias > Biomedicina
Materias > Educación Universidad Internacional Iberoamericana México > Docencia > Trabajos finales de Máster
Universidad Internacional Iberoamericana Puerto Rico > Docencia > Trabajos finales de Máster Cerrado Español Se precisa encontrar nuevos métodos de enseñanza de contenidos, especialmente en las primeras etapas de la educación. La investigación tiene como finalidad proyectar como enseñar el lenguaje a los niños desde años iniciales por medio de métodos lúdicos a traves de materiales didácticos que hacen las clases más amenas, y en un futuro crea estudiantes con buenas bases de conocimiento. metadata Lozada Rivera, Manuel Jesus mail ajesusmlr32@hotmail.com (2022) Diseño de material didáctico como herramienta para mejorar la comprensión del lengua en niños de inicial 2 de la unidad educativa “Chone”diseño de material didáctico como herramienta para mejorar la comprensión del lengua en niños de inicial 2 de la unidad educativa “Chone”. Masters thesis, SIN ESPECIFICAR.

Artículo Materias > Biomedicina
Materias > Ingeniería Universidad Europea del Atlántico > Investigación > Producción Científica
Fundación Universitaria Internacional de Colombia > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Producción Científica
Universidad Internacional Iberoamericana Puerto Rico > Investigación > Artículos y libros
Universidad Internacional do Cuanza > Investigación > Producción Científica Abierto Inglés The diagnosis of early-stage lung cancer is challenging due to its asymptomatic nature, especially given the repeated radiation exposure and high cost of computed tomography(CT). Examining the lung CT images to detect pulmonary nodules, especially the cell lung cancer lesions, is also tedious and prone to errors even by a specialist. This study proposes a cancer diagnostic model based on a deep learning-enabled support vector machine (SVM). The proposed computer-aided design (CAD) model identifies the physiological and pathological changes in the soft tissues of the cross-section in lung cancer lesions. The model is first trained to recognize lung cancer by measuring and comparing the selected profile values in CT images obtained from patients and control patients at their diagnosis. Then, the model is tested and validated using the CT scans of both patients and control patients that are not shown in the training phase. The study investigates 888 annotated CT scans from the publicly available LIDC/IDRI database. The proposed deep learning-assisted SVM-based model yields 94% accuracy for pulmonary nodule detection representing early-stage lung cancer. It is found superior to other existing methods including complex deep learning, simple machine learning, and the hybrid techniques used on lung CT images for nodule detection. Experimental results demonstrate that the proposed approach can greatly assist radiologists in detecting early lung cancer and facilitating the timely management of patients. metadata Shafi, Imran; Din, Sadia; Khan, Asim; Díez, Isabel De La Torre; Pali-Casanova, Ramón; Tutusaus, Kilian y Ashraf, Imran mail SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, ramon.pali@unini.edu.mx, kilian.tutusaus@uneatlantico.es, SIN ESPECIFICAR (2022) An Effective Method for Lung Cancer Diagnosis from CT Scan Using Deep Learning-Based Support Vector Network. Cancers, 14 (21). p. 5457. ISSN 2072-6694

Tesis Materias > Biomedicina Universidad Internacional Iberoamericana México > Docencia > Trabajos finales de Máster
Universidad Internacional Iberoamericana Puerto Rico > Docencia > Trabajos finales de Máster Cerrado Español Es primordial dentro de las instituciones de salud brindar atención de calidad a las personas que lo requieren, por ello, es fundamental que el personal de salud cuente con buen ambiente y motivación en el área laboral y más aún dentro de las áreas críticas. El presente trabajo tiene como tema “Estrategias motivacionales para el personal de enfermería que labora en áreas críticas del Hospital Verdi Cevallos Balda”, tuvo como principal objetivo proponer estrategias motivacionales para el personal de enfermería que labora en áreas críticas de la institución mencionada. La metodología utilizada fue la mixta ya que se utilizó un análisis cualitativo y cuantitativo, La técnica usada fue la encuesta aplicada a 30 licenciadas en enfermería del hospital para conocer el nivel motivacional del personal que labora en el mencionado servicio, se concluye que cuentan con un nivel motivacional aceptable, pero que puede ser mejorado. Para ello, las estrategias motivacionales desarrolladas en la presente investigación serán de gran ayuda para lograr un aumento en el desempeño laboral del personal de enfermería. metadata Pincay Ponce, Mariana Monserrate mail marielapinpon@hotmail.com (2022) Estrategias motivacionales para el personal de enfermería que labora en áreas críticas del Hospital Verdi Cevallos Balda.Noviembre2021-Enero2022. Masters thesis, SIN ESPECIFICAR.

Tesis Materias > Biomedicina Universidad Internacional Iberoamericana México > Docencia > Trabajos finales de Máster
Universidad Internacional Iberoamericana Puerto Rico > Docencia > Trabajos finales de Máster Cerrado Español El Proyecto final corresponde a la Evaluación de la calidad de servicios de atención al paciente en el consultorio privado médico-estético MEDICINESTHETIC, en la ciudad de Guayaquil durante el periodo 2020-2021; para lo cual se ha establecido como objetivo general, evaluar la calidad de servicios de atención al paciente en el consultorio privado médico-estético con el fin de aumentar la productividad empresarial mediante un plan de mejoramiento de la calidad de atención. Esto se dio por el problema identificado que se enfocó a la baja calidad de atención médica que brinda el consultorio privado, puesto que mediante la apreciación que han brindado los pacientes en sus consultas médicas ha sido insatisfactorio. Por ende, el Proyecto Final se sustentó en base a un proceso metodológico que ha facilitado la indagación y recolección de información; aquel proceso corresponde a un enfoque de tipo cualitativo y cuantitativo, de tipo descriptivo, donde se ha destacado los aspectos y características más importantes; además, se contó con el método inductivo – deductivo. Asimismo, para la aplicación del instrumento de investigación se ha considerado a 200 pacientes mayores de 18 años que son atendidos en el consultorio médico-estético, obteniendo resultados frente al grado de satisfacción, donde el 45% afirma que el consultorio se encuentra limpio y ordenado al momento de la atención; el 50% asegura que utilizan equipos modernos para la calidad del servicio; el 69% se siente satisfecho frente al servicio que esperaba y el 40% mencionó que en la primera cita el centro cumplió con las expectativas del servicio de calidad para los pacientes. Frente a estos resultados, el 45% de pacientes afirman que es conveniente diseñar un plan de mejoramiento de la calidad, puesto que con el pasar del tiempo surgen nuevas necesidades en el ámbito de la salud. Estos resultados han permitido llegar a la conclusión que las acciones necesarias para mejorar la calidad de atención, es resolver los problemas o dudas y sobre todo fortalecer el grado de confianza entre el personal y pacientes del centro médico – estético. Además, el diseño del Plan de mejoramiento de la calidad es esencial para tratar las acciones necesarias ante la productividad empresarial. metadata Sarmiento Castillo, Tania Soledad mail taniasarmientocast@gmail.com (2022) Evaluación de la calidad de servicios de atención al paciente en el consultorio privado médico-estético MEDICINESTHETIC, en la ciudad de Guayaquil durante el periodo 2020-2021. Masters thesis, SIN ESPECIFICAR.

Tesis Materias > Biomedicina Universidad Internacional Iberoamericana México > Docencia > Trabajos finales de Máster
Universidad Internacional Iberoamericana Puerto Rico > Docencia > Trabajos finales de Máster Cerrado Español El presente proyecto de investigación está orientado en la evaluación de la calidad de servicios de salud en el departamento médico, cuyos valores son la protección de la seguridad y salud de los trabajadores. En este contexto, es imprescindible crear consciencia, para mejorar la calidad del servicio, esto incluye desarrollar capacidades y habilidades del personal médico al momento de tratar enfermedades laborales en todos los ámbitos (físico, químico, mecánico, biológico, ergonómico y psicosocial). Por tanto, el objetivo de este estudio es evaluar la calidad de servicios de salud y la satisfacción del usuario en el departamento médico de la empresa Salica del Ecuador ubicado en la parroquia rural Posorja, Ecuador, durante el período agosto-septiembre 2021. Para ello, se planteó un estudio cuantitativo, con un diseño transversal, tomando como participantes a los trabajadores de la empresa que asisten al departamento médico, mismos que han aceptado participar voluntariamente. De acuerdo a los resultados del estudio se muestra un grado de satisfacción del 35% con respecto a la atención que reciben los usuarios, entre las principales cualidades destaca la empatía, seguridad y capacidad de respuesta que muestra el personal, alcanzando un grado de insatisfacción del 9% en relación a elementos tangibles y fiabilidad, ya que refieren que el consultorio no posee instalaciones atractivas y equipos modernos para el servicio médico, además, el personal no posee cualidades adecuadas para la atención de necesidades específicas de los usuarios. En conclusión, se cumplieron los objetivos del estudio, se realizó un diagnóstico situacional a través de la encuesta SERVQUAL modificada que evaluó la calidad del servicio del departamento de la empresa, identificando las principales necesidades del departamento médico, y se elaboró un plan de mejora para satisfacer las necesidades de los trabajadores. metadata Lopez Jimenez, Silvia Lisseth mail silvialj93@gmail.com (2022) Evaluación de la calidad de servicios de salud en el departamento médico de la empresa privada sálica del ecuador, ubicado en la parroquia Posorja, en el periodo de agosto y septiembre de 2021. Masters thesis, SIN ESPECIFICAR.

Artículo Materias > Biomedicina Universidad Internacional Iberoamericana Puerto Rico > Investigación > Artículos y libros Abierto Inglés Background: The rapid spread of the SARS-CoV-2 virus, especially during the first year of the COVID-19 pandemic, has caused an unprecedented health crisis worldwide. Fear of getting infected, and the high mortality rates in some places, prompted the general population to engage in self-medication practices. Methods: We conducted a cross-sectional analysis of Ecuador's prescription and self-medication consumption trends during the first two years COVID-19 pandemic. Data came from an integrated countrywide database of the physician prescribing trends, the use of over-the-counter medicines, (OTC) and the medicine-related spending levels through the COVID-19 pandemic in Ecuador. We compared the absolute difference in monthly and yearly demand and calculated excessive expenditure from previous years. Findings: We found that in Ecuador, the pre-pandemic (2017-2019) yearly expenditure among these ATC groups was, on average, $150’646,206 while during 2020 and 2021, the same groups represented $228.327.210, a significant 52% increase. Of this amount, 13% were OTC Medicines, and 87% required a formal prescription. The most remarkable growth in drug sales came from ivermectin with 2,057%, followed by hydroxychloroquine with 171%. Interpretation: Our study shows that people consumed large quantities of medicines during the first two years of the pandemic in Ecuador, including drugs with no proven benefit to treat or reduce the risk of progression due to COVID-19. We suggest that the lack of local prescription guidelines and prescription control, as well as generalized fear and misinformation led doctors and patients to prescribe and consume vast amounts of unnecessary medicines. metadata Ortiz-Prado, Esteban; Izquierdo Condoy, Juan Sebastian; Mora, Carla; Vásconez-González, Jorge y Fernández, Raúl mail SIN ESPECIFICAR (2022) Excessive Sales of Pharmaceutical Drugs in a Low and Middle-Income Country During the COVID-19 Pandemic: The Case of Ecuador. SSRN Electronic Journal. ISSN 1556-5068 (En Evaluación)

Artículo Materias > Biomedicina Universidad Internacional Iberoamericana Puerto Rico > Investigación > Artículos y libros Abierto Inglés Vaccination coverage in Ecuador has decreased since 2013, falling short of the World Health Organization’s vaccination goal. There are several causes for this deficiency in coverage, one of these are lost vaccination opportunities, which are caused when a patient without contraindications postpones, or for other reasons fails to receive a recommended immunization. The objective of this study was to determine the state of knowledge regarding vaccination contraindications among the Metropolitan District of Quito health personnel to assess missed vaccination opportunities. Through this cross-sectional descriptive study, health personnel were surveyed online and asked 18 clinical scenarios which were created to evaluate their knowledge of the true contraindications of vaccination, and measure missed opportunities. A total of 273 surveys were collected; 74% belonged to the public health system, and the rest represented by private practitioners. Of those surveyed, 98.2% of health personnel had improperly denied vaccination at least once. We specifically found vaccinations were incorrectly denied more frequently in cases where the hypothetical patient presented mild or moderate fever cases. The use of corticosteroids, autoimmune diseases, and egg allergy were also incorrectly denied (89%, 71.4%, 72.9%, and 58.6%, respectively). Among the health personnel surveyed, there is an apparent lack of knowledge of the true contraindications of vaccination and differences in knowledge about contraindications according to personnel in charge of administering immunization to children. Our preliminary results suggest that lack of education related to side effects could be biasing medical professionals’ decisions, causing them to unnecessarily delay or deny vaccinations, which likely contributes to explaining low overall vaccination coverage in Quito, the capital city of Ecuador. metadata Andrade-Guerrero, Felipe; Tapia, Adriana; Andrade, Vinicio; Vásconez-González, Jorge; Andrade-Guerrero, José; Noroña-Calvachi, Carlos; Izquierdo Condoy, Juan Sebastian; Yeager, Justin y Ortiz-Prado, Esteban mail SIN ESPECIFICAR (2022) False Contraindications for Vaccinations Result in Sub-Optimal Vaccination Coverage in Quito, Ecuador: A Cross-Sectional Study. Vaccines, 11 (1). p. 60. ISSN 2076-393X

Artículo Materias > Biomedicina
Materias > Educación física y el deporte
Materias > Alimentación Universidad Internacional Iberoamericana México > Investigación > Producción Científica
Universidad Internacional Iberoamericana Puerto Rico > Investigación > Artículos y libros Abierto Español El presente estudio tiene como objetivo determinar las relaciones entre los valores de funcionalidad motriz, estado nutricional e índices antropométricos de salud en adolescentes chilenos de 12 a 15 años. Estudio de corte transversal con una muestra no probabilística y por conveniencia, con una muestra final de 384 escolares (13,04 ± 0,85 años). Todos los participantes asistieron a dos sesiones de evaluación, donde se les realizó un registro de la historia clínica y una examinación física médica. En la segunda sesión, se realizaron evaluaciones antropométricas y las pruebas consideradas en la batería Functional Movement Screen (FMS). Los resultados muestran un 46,62% de los adolescentes posee sobrepeso y/u obesidad. El score total de FMS fue de 14,29±2,85 y se encontraron diferencias significativas en el IMC (índice de masa corporal) p=0,000 y en el peso p=0,002 según dependencia administrativa. Existe una relación entre FMS y PC (Perímetro de cintura), IMC e ICE (índice cintura estatura) (r=-0,31**p<0,003, r=-0,14**p<0,004 y r=0,38**p<0,003 respectivamente). También se encontró que aquellos escolares que presentan riesgo cardio metabólico también ostentarían un mayor riesgo relacionado con una baja calidad de la funcionalidad motriz. Se concluye que los niveles elevados de parámetros antropométricos de riesgo cardiovascular en especial el exceso de peso y el elevado perímetro de cintura se relacionan con una deficiente funcionalidad motriz. Y por otra parte se generan problemáticas cardiovasculares en esta etapa de la vida sin mayor distinción de sexo y dependencia administraba de los colegios, lo cual hace ver que la mal nutrición y la falta de actividad física impacta de manera transversal a la sociedad. metadata Rodríguez Canales, Carolina; Hinojosa Torres, Claudio; Merellano-Navarro, Eugenio; Barraza-Gómez, Fernando y Hecht-Chau, Gernot mail carolina.rodriguez@unini.org, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR (2022) Funcionalidad motriz, estado nutricional e índices antropométricos de riesgo cardiometabólico en adolescentes chilenos de 12 a 15 años. Retos: nuevas tendencias en educación f\'\isica, deporte y recreación (45). pp. 400-409.

Tesis Materias > Biomedicina
Materias > Educación Universidad Europea del Atlántico > Docencia > Trabajos finales de Máster
Universidad Internacional Iberoamericana Puerto Rico > Docencia > Trabajos finales de Máster Cerrado Español El Cáncer Cervicouterino es considerado un cáncer que sí se puede prevenir porque tiene un estado pre-invasivo prolongado y se dispone de vacunas, programas para su detección temprana, como los tamizajes y el tratamiento de las lesiones invasivas es eficaz. Su localización y frecuencia, permite su amplio estudio, pero sigue siendo un problema de salud grave. Bolivia tiene una alta incidencia y mortalidad a nivel mundial y representa un problema para la población y el desarrollo, los centros de atención de primer nivel son los que tienen la labor de ser más cercanos a la comunidad y la prevención, la prueba de tamizaje usado para la detección del cáncer de cuello uterino es el Papanicolaou, el porcentaje de pruebas realizadas es muy bajo, muy pocas usuarias acuden a realizarse el estudio, sobre todo la población joven (mujeres en edad fértil), otro de los problemas es el desconocimiento y incumplimiento de los componentes clave de la prevención, por el personal de salud. El objetivo general del presente trabajo es: Diseñar un programa de salud, para fortalecer la prevención de Cáncer Cervicouterino en el Centro de Salud Pacata, contempla un trabajo integral en un centro de primer nivel, donde se debería atender y solucionar la mayoría de las patologías, el trabajo que brinda a la población en contra de este cáncer es reduciendo el riesgo de infección por el Virus de Papiloma Humano (VPH), con información , educación, promoción, sensibilización, vacunación a niñas de 10-12 años contra el VPH y pruebas de Papanicolaou para la detección. Para conocer mejor el problema se realizó un estudio durante tres meses; los resultados dejaron al descubierto falencias tanto por parte de las beneficiarias (miedos, tabú, falta de confianza en el centro de salud, etc.), como del personal de salud (no brindar información oportuna y adecuada, falta de empatía, falta de calidad y calidez en la atención personal reducido, poner en práctica los lineamientos de prevención etc.). El presente proyecto final, tiene un enfoque profesionalizador, es un diseño de proyecto que pretende mejorar la prevención y el control del Cáncer cervicouterino. La población en estudio son mujeres usuarias del centro de salud que accedan a realizar un cuestionario de forma voluntaria y anónima el muestreo es no probabilístico. En los resultados llama la atención el hecho de que un 98% de mujeres si tiene información sobre el cáncer de cuello de útero, pero no acude al centro de salud a realizarse la detección; el 79% conoce el VPH y la prueba de diagnóstico; el 45% se realizó el PAP hace 3 años y el 5% hace 6 meses; el 63% indica que no se realizó el PAP por falta de tiempo; el 81% indica haberse realizado el PAP en otra institución de salud y no en el centro de salud; el 44% indicó que su médico le indicó realizarse el PAP; al 45% de las mujeres les entregaron el resultado del PAP en 1 semana, pero existen muchos casos en los que se demoró mucho más; el 59% indica que la falta de tiempo es un factor que impide realizarse el PAP; el 59% de las usuarias recomienda que exista celeridad en la entrega del resultado del PAP y el 22% indica que aumenten las fichas para la atención médica. Para el control, prevención y detección del cáncer cervicouterino se tiene lineamientos estratégicos, el conocimiento y cumplimiento de estas directrices nos llevaran a disminuir notablemente el Cáncer Cervicouterino en nuestro país. metadata Lima Urquizo de Mamani, Liliam mail lilita_l@hotmail.com (2022) Gestión Integral para la Prevención de Cáncer Cervicouterino en el Centro de Salud Pacata del departamento de Cochabamba-Bolivia. Masters thesis, SIN ESPECIFICAR.

Tesis Materias > Biomedicina Universidad Internacional Iberoamericana México > Docencia > Trabajos finales de Máster
Universidad Internacional Iberoamericana Puerto Rico > Docencia > Trabajos finales de Máster Cerrado Español Las infecciones nosocomiales en nuestro país son un problema de salud pública ya que eleva la tasa de mortalidad además de significar mayor gasto para el Estado debido al mayor uso de medicamentos, se alarga la estancia hospitalaria, lo que duplica o incluso triplica el gasto que representa la patología por la cual el paciente es hospitalizado. Se llama infección nosocomial a aquella que se produce dentro del ambiente hospitalario después de 48 horas de haber sido ingresado por cualquier tipo de patología. Este estudio se realizó con la revisión de las historias clínicas de los pacientes que fueron hospitalizados en el área de pediatría en el período 2019-2020, ya que con la información obtenida de las mismas se podrá evidenciar el porcentaje de infecciones nosocomiales presentadas y además es importante el tiempo de estancia hospitalaria debido a que para que una infección sea catalogada como nosocomial el paciente debe ser ingresado por más de 48 horas. Además se sabe que todo el personal de salud también se sometía con rigor a todas las medidas de bioseguridad por miedo a contagiarse de COVID 19 o de llevarlo a sus casas, además que el uso correcto de las prendas de protección era supervisado en la unidad hospitalaria y era sancionado en caso de no ser cumplidas , así mismo se implementó un protocolo para el ingreso de los pacientes a la unidad , por lo cual dicho cuidado por parte del personal de salud y de los pacientes se refleja en las historias clínicas donde se espera encontrar una disminución importante de la aparición de infecciones nosocomiales. En relación a la presencia de infecciones nosocomiales de pacientes pediátricos en los años estudiados, encontramos que en el año 2019 (prepandemia) un 55% (55/100) de los pacientes fueron afectados por infecciones nosocomiales, mientras que un 45% (45/100) no fue afectado por esta patología; mientras que en el año 2020 (pandemia) un 20% (20/100) de los pacientes fueron afectados por infecciones nosocomiales, mientras que un 80% (80/100) no fue afectado por esta patología. En este estudio se concluye que las infecciones nosocomiales son una complicación de la estancia hospitalaria prevenible mediante el correcto uso de las medidas de bioseguridad y estas son el lavado de manos constante, uso de alcohol tanto en gel como en su presentación liquida y el uso de la bata quirúrgica y mascarilla. metadata Medina Molina, Cynthia Estefania mail cynthiamedinamolina@outlook.com (2022) Influencia de las medidas de bioseguridad implementadas por la pandemia COVID19 en la disminución de infecciones nosocomiales en el área de hospitalización de Pediatría en el Hospital General Guasmo Sur, en el período 2019-2020. Masters thesis, SIN ESPECIFICAR.

Tesis Materias > Biomedicina
Materias > Educación física y el deporte
Materias > Psicología Universidad Europea del Atlántico > Docencia > Trabajos finales de Máster
Universidad Internacional Iberoamericana Puerto Rico > Docencia > Trabajos finales de Máster Cerrado Español Este trabajo tiene como propósito presentar la neurociencia aplicada al desarrollo de la capacidad de reacción en el proceso de formación de porteros, ya que este enfoque es el que orienta en la actualidad el entrenamiento deportivo, debido a las grandes posibilidades que se abren para perfeccionar las capacidades físicas y cognitivas de quienes se preparan para obtener un alto rendimiento. La neurociencia aplicada al deporte se basa en evidencias científicas que validan su aporte en la preparación de los porteros y sobre todo que incorporan una perspectiva integral del ser humano, hecho que no separa la formación física, emocional de la y cognitiva. Es decir, que se asume la formación dando la importancia a todas las dimensiones, de tal manera que el portero perfeccione no sólo sus cualidades físicas, sino también las cognitivas, aquellas que le permiten conjugar la toma de decisiones en el ejercicio de sus habilidades corporales. (Barilari, 2017)Como componente práctico de la neurociencia que estudia las acciones cerebrales, se hace visible el plan de trabajo con la Escuela de Porteros Piter Vargas, en donde, con una visión amplia de la formación de niños y jóvenes, se implementan actividades de rutina para el mejoramiento del rendimiento deportivo a nivel de reacción, percepción visual, toma de decisiones, concentración y de más funciones que se estimulan con las rutinas. metadata Vargas Bocanegra, John Piter mail danimati0112@hotmail.com (2022) La Neurociencia aplicada al desarrollo de la capacidad de reacción en el proceso de formación de porteros. Masters thesis, SIN ESPECIFICAR.

Artículo Materias > Biomedicina Universidad Internacional Iberoamericana Puerto Rico > Investigación > Artículos y libros Abierto Inglés Background: Several reports from around the world have reported that some patients who have recovered from COVID-19 have experienced a range of persistent or new clinical symptoms after a SARS-CoV-2 infection. These symptoms can last from weeks to months, impacting everyday functioning to a significant number of patients. Methods: A cross-sectional analysis based on an online, self-reporting questionnaire was conducted in Ecuador from April to July 2022. Participants were invited by social media, radio, and TV to voluntarily participate in our study. A total of 2103 surveys were included in this study. We compared socio-demographic variables and long-term persisting symptoms at low (<2500 m) and high altitude (>2500 m). Results: Overall, 1100 (52.3%) responders claimed to have Long-COVID symptoms after SARS-CoV-2 infection. Most of these were reported by women (64.0%); the most affected group was young adults between 21 to 40 years (68.5%), and most long-haulers were mestizos (91.6%). We found that high altitude residents were more likely to report persisting symptoms (71.7%) versus those living at lower altitudes (29.3%). The most common symptoms were fatigue or tiredness (8.4%), hair loss (5.1%) and difficulty concentrating (5.0%). The highest proportion of symptoms was observed in the group that received less than 2 doses. Conclusions: This is the first study describing post-COVID symptoms’ persistence in low and high-altitude residents. Our findings demonstrate that women, especially those aging between 21–40, are more likely to describe Long-COVID. We also found that living at a high altitude was associated with higher reports of mood changes, tachycardia, decreased libido, insomnia, and palpitations compared to lowlanders. Finally, we found a greater risk to report Long-COVID symptoms among women, those with previous comorbidities and those who had a severer acute SARS-CoV-2 infection. metadata Izquierdo Condoy, Juan Sebastian; Fernandez-Naranjo, Raul; Vasconez-González, Eduardo; Cordovez, Simone; Tello-De-la-Torre, Andrea; Paz, Clara; Delgado-Moreira, Karen; Carrington, Sarah; Viscor, Ginés y Ortiz-Prado, Esteban mail SIN ESPECIFICAR (2022) Long COVID at Different Altitudes: A Countrywide Epidemiological Analysis. International Journal of Environmental Research and Public Health, 19 (22). p. 14673. ISSN 1660-4601

Artículo Materias > Biomedicina
Materias > Ingeniería Universidad Europea del Atlántico > Investigación > Producción Científica
Fundación Universitaria Internacional de Colombia > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Producción Científica
Universidad Internacional Iberoamericana Puerto Rico > Investigación > Artículos y libros
Universidad Internacional do Cuanza > Investigación > Producción Científica Abierto Inglés Mobility and low energy consumption are considered the main requirements for wireless body area sensor networks (WBASN) used in healthcare monitoring systems (HMS). In HMS, battery-powered sensor nodes with limited energy are used to obtain vital statistics about the body. Hence, energy-efficient schemes are desired to maintain long-term and steady connectivity of the sensor nodes. A sheer amount of energy is consumed in activities such as idle listening, excessive transmission and reception of control messages, packet collisions and retransmission of packets, and poor path selection, that may lead to more energy consumption. A combination of adaptive scheduling with an energy-efficient protocol can help select an appropriate path at a suitable time to minimize the control overhead, energy consumption, packet collision, and excessive idle listening. This paper proposes a region-based energy-efficient multipath routing (REMR) approach that divides the entire sensor network into clusters with preferably multiple candidates to represent each cluster. The cluster representatives (CRs) route packets through various clusters. For routing, the energy requirement of each route is considered, and the path with minimum energy requirements is selected. Similarly, end-to-end delay, higher throughput, and packet-delivery ratio are considered for packet routing. metadata Akbar, Shuja; Mehdi, Muhammad Mohsin; Jamal, M. Hasan; Raza, Imran; Hussain, Syed Asad; Breñosa, Jose; Martínez Espinosa, Julio César; Pascual Barrera, Alina Eugenia y Ashraf, Imran mail SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, josemanuel.brenosa@uneatlantico.es, ulio.martinez@unini.edu.mx, alina.pascual@unini.edu.mx, SIN ESPECIFICAR (2022) Multipath Routing in Wireless Body Area Sensor Network for Healthcare Monitoring. Healthcare, 10 (11). p. 2297. ISSN 2227-9032

Artículo Materias > Biomedicina
Materias > Ingeniería Universidad Europea del Atlántico > Investigación > Producción Científica
Universidad Internacional Iberoamericana Puerto Rico > Investigación > Artículos y libros
Universidad Internacional do Cuanza > Investigación > Producción Científica Abierto Inglés The prevalence of anxiety among university students is increasing, resulting in the negative impact on their academic and social (behavioral and emotional) development. In order for students to have competitive academic performance, the cognitive function should be strengthened by detecting and handling anxiety. Over a period of 6 weeks, this study examined how to detect anxiety and how Mano Shakti Yoga (MSY) helps reduce anxiety. Relying on cardiac signals, this study follows an integrated detection-estimation-reduction framework for anxiety using the Intelligent Internet of Medical Things (IIoMT) and MSY. IIoMT is the integration of Internet of Medical Things (wearable smart belt) and machine learning algorithms (Decision Tree (DT), Random Forest (RF), and AdaBoost (AB)). Sixty-six eligible students were selected as experiencing anxiety detected based on the results of self-rating anxiety scale (SAS) questionnaire and a smart belt. Then, the students were divided randomly into two groups: experimental and control. The experimental group followed an MSY intervention for one hour twice a week, while the control group followed their own daily routine. Machine learning algorithms are used to analyze the data obtained from the smart belt. MSY is an alternative improvement for the immune system that helps reduce anxiety. All the results illustrate that the experimental group reduced anxiety with a significant (p < 0.05) difference in group × time interaction compared to the control group. The intelligent techniques achieved maximum accuracy of 80% on using RF algorithm. Thus, students can practice MSY and concentrate on their objectives by improving their intelligence, attention, and memory. metadata Pal, Rishi; Adhikari, Deepak; Heyat, Md Belal Bin; Guragai, Bishal; Lipari, Vivian; Brito Ballester, Julién; De la Torre Díez, Isabel; Abbas, Zia y Lai, Dakun mail SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, vivian.lipari@uneatlantico.es, julien.brito@uneatlantico.es, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR (2022) A Novel Smart Belt for Anxiety Detection, Classification, and Reduction Using IIoMT on Students’ Cardiac Signal and MSY. Bioengineering, 9 (12). p. 793. ISSN 2306-5354

Artículo Materias > Biomedicina Universidad Internacional Iberoamericana Puerto Rico > Investigación > Artículos y libros Abierto Inglés Objective To compare the predictive value of the quick COVID-19 Severity Index (qCSI) and the National Early Warning Score (NEWS) for 90-day mortality amongst COVID-19 patients. Methods Multicenter retrospective cohort study conducted in adult patients transferred by ambulance to an emergency department (ED) with suspected COVID-19 infection subsequently confirmed by a SARS-CoV-2 test (polymerase chain reaction). We collected epidemiological data, clinical covariates (respiratory rate, oxygen saturation, systolic blood pressure, heart rate, temperature, level of consciousness and use of supplemental oxygen) and hospital variables. The primary outcome was cumulative all-cause mortality during a 90-day follow-up, with mortality assessment monitoring time points at 1, 2, 7, 14, 30 and 90 days from ED attendance. Comparison of performances for 90-day mortality between both scores was carried out by univariate analysis. Results From March to November 2020, we included 2,961 SARS-CoV-2 positive patients (median age 79 years, IQR 66–88), with 49.2% females. The qCSI score provided an AUC ranging from 0.769 (1-day mortality) to 0.749 (90-day mortality), whereas AUCs for NEWS ranging from 0.825 for 1-day mortality to 0.777 for 90-day mortality. At all-time points studied, differences between both scores were statistically significant (p < .001). Conclusion Patients with SARS-CoV-2 can rapidly develop bilateral pneumonias with multiorgan disease; in these cases, in which an evacuation by the EMS is required, reliable scores for an early identification of patients with risk of clinical deterioration are critical. The NEWS score provides not only better prognostic results than those offered by qCSI at all the analyzed time points, but it is also better suited for COVID-19 patients. metadata Martín-Rodríguez, Francisco; Sanz-García, Ancor; Ortega, Guillermo J.; Delgado-Benito, Juan F.; Garcia Villena, Eduardo; Mazas Pérez-Oleaga, Cristina; López-Izquierdo, Raúl y Castro Villamor, Miguel A. mail SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, eduardo.garcia@uneatlantico.es, cristina.mazas@uneatlantico.es, SIN ESPECIFICAR, SIN ESPECIFICAR (2022) One-on-one comparison between qCSI and NEWS scores for mortality risk assessment in patients with COVID-19. Annals of Medicine, 54 (1). pp. 646-654. ISSN 0785-3890

Artículo Materias > Biomedicina
Materias > Alimentación Universidad Europea del Atlántico > Investigación > Producción Científica
Fundación Universitaria Internacional de Colombia > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Producción Científica
Universidad Internacional Iberoamericana Puerto Rico > Investigación > Artículos y libros
Universidad Internacional do Cuanza > Investigación > Producción Científica Cerrado Inglés Cactus has been used in traditional folk medicine because of its role in treating a number of diseases and conditions. Prickly pear fruit is an excellent source of secondary metabolites (i.e., betalains, flavonoids, and ascorbic acid) with health-promoting properties against many common human diseases, including diabetes, hypertension, hypercholesterolemia, rheumatic pain, gastric mucosa diseases and asthma. In addition, prickly pears are potential candidates for the development of low-cost functional foods because they grow with low water requirements in arid regions of the world. This review describes the main bioactive compounds found in this fruit and shows the in vitro and some clinical studies about the fruit of most important cactus (Opuntia ficus-indica) and its relationship with some chronic diseases. Even though a lot of effort have been done to study the relationship between this fruit and the human health, more studies on Opuntia ficus-indica could help better understand its pharmacological mechanism of action to provide clear scientific evidence to explain its traditional uses, and to identify its therapeutic potential in other diseases. metadata Armas Diaz, Yasmany; Machì, Michele; Salinari, Alessia; Mazas Pérez-Oleaga, Cristina; Martínez López, Nohora Milena; Briones Urbano, Mercedes y Cianciosi, Danila mail SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, cristina.mazas@uneatlantico.es, nohora.martinez@uneatlantico.es, mercedes.briones@uneatlantico.es, SIN ESPECIFICAR (2022) Prickly pear fruits from "Opuntia ficus-indica" varieties as a source of potential bioactive compounds in the Mediterranean diet. Mediterranean Journal of Nutrition and Metabolism, 15 (4). pp. 581-592. ISSN 1973798X

Tesis Materias > Biomedicina
Materias > Psicología
Materias > Ciencias Sociales Universidad Europea del Atlántico > Docencia > Trabajos finales de Máster
Universidad Internacional Iberoamericana Puerto Rico > Docencia > Trabajos finales de Máster Cerrado Español Los colaboradores del área de producción de una empresa industrial están expuestos a múltiples factores de riesgo que pueden perjudicar su productividad. Es por esto que se hace necesario determinar los principales factores de riesgo en el área de producción de la empresa mediante un análisis de las condiciones laborales que permita mejorar la productividad y la eficiencia de los procesos. Las empresas industriales están expuestas a múltiples riesgos que pueden representan pérdidas significativas en términos económicos, además de exponer a los trabajadores a condiciones peligrosas para su integridad física y mental. Se hace necesario diseñar un ambiente laboral que permita incrementar la eficiencia de los procesos y garantizar la integridad de cada uno de los involucrados en la gestión de los mismos. Las actividades de seguridad e higiene son elementos que se necesitan para asegurar la disponibilidad de las habilidades y actitudes de los colaboradores. Actualmente, la salud y seguridad de los empleados constituye una de las principales actividades en la prevención adecuada de la fuerza laboral. Por lo tanto, métodos adecuados de trabajo, donde estén claramente definidas, las condiciones de trabajo y una estrategia para la de prevención de riesgos laborales de acuerdo a sus necesidades. La presente investigación tiene un carácter descriptivo. El tipo de análisis que se utilizará es la acción participativa en la investigación. Por otra parte, la población a estudiar corresponde a los colaboradores de la empresa industrial que se eligió para el proyecto. Esta población es de aproximadamente 120 empleados en total. De aquí se tomará la muestra correspondiente. Dicha muestra se obtendrá mediante un muestreo probabilístico. Una vez elegida, se procederá a recolectar los datos y a detallar los resultados obtenidos. De tal manera que se puedan proponer acciones de mejora para los procesos de la empresa. metadata Areiza Roman, Yamile Tatiana mail tatayami23@hotmail.com (2022) Principales factores de riesgo a los que están expuestos los colaboradores del área de producción de una empresa industrial. Masters thesis, Universidad Europea del Atlántico.

Tesis Materias > Biomedicina Universidad Internacional Iberoamericana México > Docencia > Trabajos finales de Máster
Universidad Internacional Iberoamericana Puerto Rico > Docencia > Trabajos finales de Máster Cerrado Español Introducción: La satisfacción del usuario es un indicador de la calidad de la atención brindada y es importante evaluarla e identificar áreas de mejora para optimizar la calidad asistencial. Las investigaciones sobre este tema han mostrado recientemente la fidelidad en la atención, por ende, el presente estudio estuvo enfocado en describir la satisfacción de los usuarios hospitalizados en el Instituto de Neurociencias de la ciudad de Guayaquil, Ecuador en los años 2019 y 2020.Metodología: La investigación se desarrolló bajo una metodología cuantitativa tipo transversal dirigida a 1801 sujetos hospitalizados en el Instituto de Neurociencias de la ciudad de Guayaquil durante el periodo 2019 y 2020 a través de 2 cuestionarios estructurados para evaluar el nivel de satisfacción de los pacientes, los cuales fueron analizados a través del programa SPSS y Excel para los resultados estadísticos. Resultados: elementos tangibles: satisfechos en un 46,1% vs 18% insatisfechos, empatía con un 42,4% de pacientes satisfechos vs 15,3% insatisfechos. Fiabilidad, 36,1% vs 18% insatisfechos. Capacidad de respuesta: 39% vs 16,3% insatisfechos y elementos de seguridad el 39,5% de los usuarios estuvieron satisfechos vs 17,8% insatisfechos. Conclusiones: En términos generales se puede deducir que, el nivel de satisfacción expresado por los pacientes en el presente estudio estuvo relacionado con el cuidado y la atención recibida, el cual caracteriza a la institución como un centro sanitario que proporciona calidad asistencial, sin embargo, requiere de nuevas mejoras en las áreas vulneradas. metadata Estrella Almeida, Diego Javier mail djeadiego@hotmail.com (2022) Satisfacción de los usuarios hospitalizados en el Instituto de Neurociencias de la ciudad de Guayaquil, Ecuador en los años 2019 y 2020. Masters thesis, SIN ESPECIFICAR.

Tesis Materias > Biomedicina Universidad Internacional Iberoamericana México > Docencia > Trabajos finales de Máster
Universidad Internacional Iberoamericana Puerto Rico > Docencia > Trabajos finales de Máster Cerrado Español Objetivo general: Analizar el nivel de satisfacción laboral de los médicos rurales del primer nivel de atención de salud del Ministerios de Salud Pública, Ecuador, en el periodo febrero – marzo 2022. Enfoques teóricos: La satisfacción laboral es tomada como una sensación positiva por parte del individuo hacia su trabajo. Herzberg propuso que la satisfacción laboral posee componentes extrínsecos e intrínsecos. El servicio social obligatorio (medicatura rural) resulta fundamental para el primer nivel de atención representando un componente esencial para brindar atención médica a poblaciones que habitan en zonas rurales con áreas de difícil y muy difícil acceso. Metodología utilizada: Se realizó un estudio cuantitativo, descriptivo, de corte transversal en médicos rurales del Ministerio de Salud Pública de Ecuador utilizando una encuesta en línea autoadministrada, conformado por preguntas que evaluaron datos demográficos y el cuestionario de satisfacción laboral S20/23 validado. Se llevó a cabo análisis descriptivo univarial utilizando frecuencias y porcentajes para variables cualitativas, así como, media y desviación estándar (DE) para variables cuantitativas. El análisis bivarial se realizó utilizando la prueba de asociación Chi-2, valores de p<0.05 se aceptaron como estadísticamente significativos.Resultados: Respecto al sexo se vio un predominio de población femenina con 61% (n=150), mientras un 39% de población masculina (n=97). la satisfacción laboral global en los médicos rurales mostró tener una puntuación media de 4,1. Los factores con mayor satisfacción fueron la satisfacción con la supervisión, con el ambiente, con la participación y satisfacción intrínseca, el factor de beneficios 43,3% (n = 107) refirieron sentirse insatisfechos.Conclusiones: La satisfacción laboral de los médicos rurales de primer nivel de atención de salud en Ecuador en el periodo febrero – marzo 2022 tuvo una puntuación promedio de 4,1 “indiferente”. Los médicos rurales de Ecuador solteros, que trabajan en Centro de Salud tipo B, en la región Amazónica y con jornadas de trabajo de 22 días de trabajo continuos y 8 días de descanso mostraron niveles de satisfacción laboral más altos, ninguna de estas diferencias fue estadísticamente significativa. metadata Izquierdo Condoy, Juan Sebastian mail juan1izquierdo11@gmail.com (2022) Satisfacción laboral en médicos rurales del primer nivel de atención de salud del Ministerio de Salud Pública, Ecuador, en el periodo febrero – marzo 2022. Masters thesis, SIN ESPECIFICAR.

Artículo Materias > Biomedicina Universidad Internacional Iberoamericana Puerto Rico > Investigación > Artículos y libros Abierto Inglés COVID-19 made its debut as a pandemic in 2020; since then, more than 607 million cases and at least 6.5 million deaths have been reported worldwide. While the burden of disease has been described, the long-term effects or chronic sequelae are still being clarified. The aim of this study was to present an overview of the information available on the sequelae of COVID-19 in people who have suffered from the infection. A systematic review was carried out in which cohort studies, case series, and clinical case reports were included, and the PubMed, Scielo, SCOPUS, and Web of Science databases were extracted. Information was published from 2020 to 1 June 2022, and we included 26 manuscripts: 9 for pulmonary, 6 for cardiac, 2 for renal, 8 for neurological and psychiatric, and 6 for cutaneous sequelae. Studies showed that the most common sequelae were those linked to the lungs, followed by skin, cutaneous, and psychiatric alterations. Women reported a higher incidence of the sequelae, as well as those with comorbidities and more severe COVID-19 history. The COVID-19 pandemic has not only caused death and disease since its appearance, but it has also sickened millions of people around the globe who potentially suffer from serious illnesses that will continue to add to the list of health problems, and further burden healthcare systems around the world. metadata Vásconez-González, Jorge; Izquierdo Condoy, Juan Sebastian; Fernandez-Naranjo, Raul y Ortiz-Prado, Esteban mail SIN ESPECIFICAR (2022) A Systematic Review and Quality Evaluation of Studies on Long-Term Sequelae of COVID-19. Healthcare, 10 (12). p. 2364. ISSN 2227-9032

Tesis Materias > Biomedicina
Materias > Ingeniería Universidad Europea del Atlántico > Docencia > Trabajos finales de Máster
Universidad Internacional Iberoamericana Puerto Rico > Docencia > Trabajos finales de Máster Cerrado Español De acuerdo con el Decreto 1072 de 2015 el empleador o contratante debe aplicar una metodología para identificar los peligros y evaluar los riesgos en seguridad y salud en el trabajo, con la finalidad de que puedan priorizar y establecer los controles necesarios. Esta metodología debe ser sistemática, que tenga alcance sobre todos los procesos, actividades y centros de trabajo de la empresa, así como de los trabajadores independientemente de su forma de contratación o vinculación. El presente proyecto de investigación es un estudio de caso enfocado a un taller de Ebanistería en la ciudad de Sincelejo Sucre, debido a que existen muchos talleres de ebanistería de carácter familiar en los hogares, siendo estos la principal fuente económica de ingresos, sin embargo, estos talleres no cuentan con formación y entrenamiento en materia de prevención de riesgos laborales. El objetivo general del estudio es valorar los riesgos laborales para el establecimiento de medidas de intervención y control de los peligros presentes en un taller de Ebanistería de la ciudad de Sincelejo, Sucre. La metodología utilizada fue cualitativa con diseño de investigación descriptivo de tipo investigación acción y de corte transversal. Los peligros identificados fueron: físicos, químicos, biológicos, biomecánicos, psicosociales, de seguridad, tales como eléctricos, mecánicos, locativos en niveles de riesgo alto y muy alto con criterios no aceptables o aceptables con control especifico. De acuerdo con los resultados, se establecieron medidas de intervención como sustitución, controles de ingeniería, administrativos y elementos de protección personal. En las actividades de ebanistería y carpintería, las medidas preventivas frente a los riesgos son bajas o nulas, conllevando a que los trabajadores sean vulnerables y mayormente expuestos a los peligros, debido a que, por ser talleres informales en casa desconocen los riesgos y consecuencias que trae consigo las tareas propias de la transformación de la madera, la utilización de herramientas, máquinas y equipos con alta peligrosidad. Por tal razón es importante que se implementen medidas de prevención y control de los peligros a los cuales están expuestos los trabajadores, así como la capacitación y entrenamiento en la promoción de conductas de autocuidado. metadata Gonzalez Monterrosa, Ana Isabel mail ana-isa-26@hotmail.com (2022) Valoración de riesgos laborales para el establecimiento de medidas de intervención y control de los peligros en un taller de Ebanistería de la ciudad de Sincelejo, Sucre. Masters thesis, SIN ESPECIFICAR.

Artículo Materias > Biomedicina
Materias > Ciencias Sociales Universidad Internacional Iberoamericana Puerto Rico > Investigación > Artículos y libros Abierto Inglés Background Despite worldwide progress in terms of clean water supply, sanitation, and hygiene knowledge, some middle and most of low-income countries are still experiencing many diseases transmitted using unsafe water and the lack of sanitation. Methods To understand the impact of all waterborne diseases (WBD) registered in Ecuador. We performed a population-based analysis of all cases and deaths due to WBD in Ecuador based on the national public databases of hospital discharges as a proxy of incidence, in-hospital mortality, and countrywide general mortality rates from 2011 to 2020. Results In Ecuador, mestizos (mixed European and Indigenous American ancestry) had the greatest morbidity rate (141/100,000), followed by indigenous (63/100,000) and self-determined white patients (21/100,000). However, in terms of mortality, indigenous population have the greatest risk and rates, having a 790% additional mortality rate (2.6/100,000) than the reference group (self-determined white populations) at 0.29/100,000. The burden of disease analysis demonstrated that indigenous had the highest burden of disease caused by WBD with 964 YLL per every 100,000 people while mestizos have 360 YYL per 100,000 and self-determined white Ecuadorians have 109 YYL per 100,000. Conclusions In Ecuador, waterborne diseases (WBD) are still a major public health problem. We found that indigenous population had higher probability of getting sick and die due to WBD than the rest of the ethnic groups in Ecuador. We also found that younger children and the elderly are more likely to be admitted to the hospital due to a WBD. These epidemiological trends are probably associated with the lower life expectancy found among Indigenous than among the rest of the ethnic groups, who die at least, 39 years earlier than the self-determined white populations, 28 years earlier than Afro-Ecuadorians and 12 years earlier than the mestizos. metadata Ortiz-Prado, Esteban; Simbaña-Rivera, Katherine; Cevallos, Gabriel; Gómez-Barreno, Lenin; Cevallos, Domenica; Lister, Alex; Fernandez-Naranjo, Raul; Ríos-Touma, Blanca; Vásconez-González, Jorge y Izquierdo Condoy, Juan Sebastian mail SIN ESPECIFICAR (2022) Waterborne diseases and ethnic-related disparities: A 10 years nationwide mortality and burden of disease analysis from Ecuador. Frontiers in Public Health, 10. ISSN 2296-2565

Artículo Materias > Biomedicina
Materias > Ciencias Sociales Universidad Internacional Iberoamericana Puerto Rico > Investigación > Artículos y libros Abierto Inglés Background Despite worldwide progress in terms of clean water supply, sanitation, and hygiene knowledge, some middle and most of low-income countries are still experiencing many diseases transmitted using unsafe water and the lack of sanitation. Methods To understand the impact of all waterborne diseases (WBD) registered in Ecuador, we performed an analysis of all cases and deaths related to WBD to compute incidence and mortality rates. Results We found that in Ecuador, mestizo people had the greatest morbidity rate (141/100,000) patient followed by indigenous (63/100,000) and self-determined white patients (21/100,000). However, in terms of mortality, indigenous population have a 790% increase in mortality rate (2.6 /100,000) when compared to self-determined white populations (0.29/100,000) or 176% more when compared to mestizos (0.94/100,000). This trend remains the same among children and the elderly who have higher mortality rates when compared to other ethnic groups. Conclusions In Ecuador, water borne diseases (WBD) are still a major public health problem. We found that younger children and elderly are more likely to be get sick and die due to water borne diseases. In terms of morbidity, mestizos reported the highest rate, while in terms of mortality, indigenous populations are the most affected, having the highest mortality among different ethnic groups. We hypostatize that reduced health care access is linked to fewer reporting incidence rates among indigenous populations but higher mortality rates. metadata Ortiz-Prado, Esteban; Simbaña-Rivera, Katherine; Cevallos-Sierra, Gabriel; Cevallos, Domenica; Lister, Alex; Fernandez-Naranjo, Raul; Ríos-Touma, Blanca; Vasconez, Jorge; Izquierdo Condoy, Juan Sebastian y Gomez-Barreno, Lenin mail SIN ESPECIFICAR (2022) Waterborne diseases as an indicator of health disparities: A nationwide study of WaSH related morbidity and mortality in Ecuador from 2011-2020. Research square. (Inédito)

Artículo Materias > Biomedicina
Materias > Ingeniería Universidad Europea del Atlántico > Investigación > Producción Científica
Universidad Internacional Iberoamericana Puerto Rico > Investigación > Artículos y libros
Universidad Internacional do Cuanza > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Producción Científica Abierto Inglés White blood cell (WBC) type classification is a task of significant importance for diagnosis using microscopic images of WBC, which develop immunity to fight against infections and foreign substances. WBCs consist of different types, and abnormalities in a type of WBC may potentially represent a disease such as leukemia. Existing studies are limited by low accuracy and overrated performance, often caused by model overfit due to an imbalanced dataset. Additionally, many studies consider a lower number of WBC types, and the accuracy is exaggerated. This study presents a hybrid feature set of selective features and synthetic minority oversampling technique-based resampling to mitigate the influence of the above-mentioned problems. Furthermore, machine learning models are adopted for being less computationally complex, requiring less data for training, and providing robust results. Experiments are performed using both machine- and deep learning models for performance comparison using the original dataset, augmented dataset, and oversampled dataset to analyze the performances of the models. The results suggest that a hybrid feature set of both texture and RGB features from microscopic images, selected using Chi2, produces a high accuracy of 0.97 with random forest. Performance appraisal using k-fold cross-validation and comparison with existing state-of-the-art studies shows that the proposed approach outperforms existing studies regarding the obtained accuracy and computational complexity. metadata Rustam, Furqan; Aslam, Naila; De La Torre Díez, Isabel; Khan, Yaser Daanial; Vidal Mazón, Juan Luis; Rodríguez Velasco, Carmen Lilí y Ashraf, Imran mail SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, juanluis.vidal@uneatlantico.es, carmen.rodriguez@uneatlantico.es, SIN ESPECIFICAR (2022) White Blood Cell Classification Using Texture and RGB Features of Oversampled Microscopic Images. Healthcare, 10 (11). p. 2230. ISSN 2227-9032

2021

Tesis Materias > Biomedicina Universidad Internacional Iberoamericana México > Docencia > Trabajos finales de Máster
Universidad Internacional Iberoamericana Puerto Rico > Docencia > Trabajos finales de Máster Cerrado Español La presente investigación, evidencia como problemática el bajo rendimiento del personal de enfermería en el cuidado directo de los usuarios, por lo cual, es necesario que se plantee el conocimiento científico necesario del estrés laboral en el personal de enfermería del servicio de Neurología del Hospital de Especialidades Carlos Andrade Marín con el que se desarrolle un plan que sirva como estrategia preventiva para disminuir o prevenir el estrés laboral en el personal de enfermería en la ciudad de Quito, Ecuador en el periodo de Mayo – Noviembre 2021. La metodología se basa en un enfoque cuantitativo de corte transversal que permitió que los resultados sean analizados de manera numérica por lo que se lo realizo un criterio descriptivo, así mismo, para la obtención de información de la presente investigación se aplicó una encuesta personal a 20 licenciadas de enfermería entre 30 – 60 años, que laboran en el servicio de Neurología que fue objeto de estudio para posteriormente analizarlas. De este modo se determinó que diferentes factores inciden y provocan estrés en el personal. El 55% del personal afirmó que cualquier organización bajo condiciones estresantes en el lugar de trabajo afecta sus resultados de producción, siendo menos competitivo en el mercado y conlleva consecuencias como falta de dedicación y fallas en el desempeño. Concluyendo que si presentan estrés laboral por la intervención de los factores psicosociales como síntomas deficientes que afectan a las enfermeras en su gestión laboral producto de las cargas excesivas de trabajo, gestión deficiente de la organización y la comunicación. metadata Simaliza Romero, Maria Teresa mail maytere88@gmail.com (2021) Plan estratégico preventivo para reducir el estrés laboral en el personal de enfermería del servicio de Neurología del Hospital de Especialidades Carlos Andrade Marín de la ciudad de Quito en el periodo de Mayo – Noviembre 2021. Masters thesis, Universidad Internacional Iberoamericana México.

2015

Este listado fue generado el Fri Dec 20 23:50:58 2024 UTC.

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Influence of E-learning training on the acquisition of competences in basketball coaches in Cantabria

The main aim of this study was to analyse the influence of e-learning training on the acquisition of competences in basketball coaches in Cantabria. The current landscape of basketball coach training shows an increasing demand for innovative training models and emerging pedagogies, including e-learning-based methodologies. The study sample consisted of fifty students from these courses, all above 16 years of age (36 males, 14 females). Among them, 16% resided outside the autonomous community of Cantabria, 10% resided more than 50 km from the city of Santander, 36% between 10 and 50 km, 14% less than 10 km, and 24% resided within Santander city. Data were collected through a Google Forms survey distributed by the Cantabrian Basketball Federation to training course students. Participation was voluntary and anonymous. The survey, consisting of 56 questions, was validated by two sports and health doctors and two senior basketball coaches. The collected data were processed and analysed using Microsoft® Excel version 16.74, and the results were expressed in percentages. The analysis revealed that 24.60% of the students trained through the e-learning methodology considered themselves fully qualified as basketball coaches, contrasting with 10.98% of those trained via traditional face-to-face methodology. The results of the study provide insights into important characteristics that can be adjusted and improved within the investigated educational process. Moreover, the study concludes that e-learning training effectively qualifies basketball coaches in Cantabria.

Producción Científica

Josep Alemany Iturriaga mail josep.alemany@uneatlantico.es, Álvaro Velarde-Sotres mail alvaro.velarde@uneatlantico.es, Javier Jorge mail , Kamil Giglio mail ,

Alemany Iturriaga

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Smart agriculture: utilizing machine learning and deep learning for drought stress identification in crops

Plant stress reduction research has advanced significantly with the use of Artificial Intelligence (AI) techniques, such as machine learning and deep learning. This is a significant step toward sustainable agriculture. Innovative insights into the physiological responses of plants mostly crops to drought stress have been revealed through the use of complex algorithms like gradient boosting, support vector machines (SVM), recurrent neural network (RNN), and long short-term memory (LSTM), combined with a thorough examination of the TYRKC and RBR-E3 domains in stress-associated signaling proteins across a range of crop species. Modern resources were used in this study, including the UniProt protein database for crop physiochemical properties associated with specific signaling domains and the SMART database for signaling protein domains. These insights were then applied to deep learning and machine learning techniques after careful data processing. The rigorous metric evaluations and ablation analysis that typified the study’s approach highlighted the algorithms’ effectiveness and dependability in recognizing and classifying stress events. Notably, the accuracy of SVM was 82%, while gradient boosting and RNN showed 96%, and 94%, respectively and LSTM obtained an astounding 97% accuracy. The study observed these successes but also highlights the ongoing obstacles to AI adoption in agriculture, emphasizing the need for creative thinking and interdisciplinary cooperation. In addition to its scholarly value, the collected data has significant implications for improving resource efficiency, directing precision agricultural methods, and supporting global food security programs. Notably, the gradient boosting and LSTM algorithm outperformed the others with an exceptional accuracy of 96% and 97%, demonstrating their potential for accurate stress categorization. This work highlights the revolutionary potential of AI to completely disrupt the agricultural industry while simultaneously advancing our understanding of plant stress responses.

Producción Científica

Tariq Ali mail , Saif Ur Rehman mail , Shamshair Ali mail , Khalid Mahmood mail , Silvia Aparicio Obregón mail silvia.aparicio@uneatlantico.es, Rubén Calderón Iglesias mail ruben.calderon@uneatlantico.es, Tahir Khurshaid mail , Imran Ashraf mail ,

Ali

open

Carotenoids Intake and Cardiovascular Prevention: A Systematic Review

Background: Cardiovascular diseases (CVDs) encompass a variety of conditions that affect the heart and blood vessels. Carotenoids, a group of fat-soluble organic pigments synthesized by plants, fungi, algae, and some bacteria, may have a beneficial effect in reducing cardiovascular disease (CVD) risk. This study aims to examine and synthesize current research on the relationship between carotenoids and CVDs. Methods: A systematic review was conducted using MEDLINE and the Cochrane Library to identify relevant studies on the efficacy of carotenoid supplementation for CVD prevention. Interventional analytical studies (randomized and non-randomized clinical trials) published in English from January 2011 to February 2024 were included. Results: A total of 38 studies were included in the qualitative analysis. Of these, 17 epidemiological studies assessed the relationship between carotenoids and CVDs, 9 examined the effect of carotenoid supplementation, and 12 evaluated dietary interventions. Conclusions: Elevated serum carotenoid levels are associated with reduced CVD risk factors and inflammatory markers. Increasing the consumption of carotenoid-rich foods appears to be more effective than supplementation, though the specific effects of individual carotenoids on CVD risk remain uncertain.

Producción Científica

Sandra Sumalla Cano mail sandra.sumalla@uneatlantico.es, Imanol Eguren García mail imanol.eguren@uneatlantico.es, Álvaro Lasarte García mail , Thomas Prola mail thomas.prola@uneatlantico.es, Raquel Martínez Díaz mail raquel.martinez@uneatlantico.es, Iñaki Elío Pascual mail inaki.elio@uneatlantico.es,

Sumalla Cano

open

StackIL10: A stacking ensemble model for the improved prediction of IL-10 inducing peptides

Interleukin-10, a highly effective cytokine recognized for its anti-inflammatory properties, plays a critical role in the immune system. In addition to its well-documented capacity to mitigate inflammation, IL-10 can unexpectedly demonstrate pro-inflammatory characteristics under specific circumstances. The presence of both aspects emphasizes the vital need to identify the IL-10-induced peptide. To mitigate the drawbacks of manual identification, which include its high cost, this study introduces StackIL10, an ensemble learning model based on stacking, to identify IL-10-inducing peptides in a precise and efficient manner. Ten Amino-acid-composition-based Feature Extraction approaches are considered. The StackIL10, stacking ensemble, the model with five optimized Machine Learning Algorithm (specifically LGBM, RF, SVM, Decision Tree, KNN) as the base learners and a Logistic Regression as the meta learner was constructed, and the identification rate reached 91.7%, MCC of 0.833 with 0.9078 Specificity. Experiments were conducted to examine the impact of various enhancement techniques on the correctness of IL-10 Prediction. These experiments included comparisons between single models and various combinations of stacking-based ensemble models. It was demonstrated that the model proposed in this study was more effective than singular models and produced satisfactory results, thereby improving the identification of peptides that induce IL-10.

Producción Científica

Salman Sadullah Usmani mail , Izaz Ahmmed Tuhin mail , Md. Rajib Mia mail , Md. Monirul Islam mail , Imran Mahmud mail , Carlos Eduardo Uc Ríos mail carlos.uc@unini.edu.mx, Henry Fabian Gongora mail henry.gongora@uneatlantico.es, Imran Ashraf mail , Md. Abdus Samad mail ,

Usmani

open

Roman urdu hate speech detection using hybrid machine learning models and hyperparameter optimization

With the rapid increase of users over social media, cyberbullying, and hate speech problems have arisen over the past years. Automatic hate speech detection (HSD) from text is an emerging research problem in natural language processing (NLP). Researchers developed various approaches to solve the automatic hate speech detection problem using different corpora in various languages, however, research on the Urdu language is rather scarce. This study aims to address the HSD task on Twitter using Roman Urdu text. The contribution of this research is the development of a hybrid model for Roman Urdu HSD, which has not been previously explored. The novel hybrid model integrates deep learning (DL) and transformer models for automatic feature extraction, combined with machine learning algorithms (MLAs) for classification. To further enhance model performance, we employ several hyperparameter optimization (HPO) techniques, including Grid Search (GS), Randomized Search (RS), and Bayesian Optimization with Gaussian Processes (BOGP). Evaluation is carried out on two publicly available benchmarks Roman Urdu corpora comprising HS-RU-20 corpus and RUHSOLD hate speech corpus. Results demonstrate that the Multilingual BERT (MBERT) feature learner, paired with a Support Vector Machine (SVM) classifier and optimized using RS, achieves state-of-the-art performance. On the HS-RU-20 corpus, this model attained an accuracy of 0.93 and an F1 score of 0.95 for the Neutral-Hostile classification task, and an accuracy of 0.89 with an F1 score of 0.88 for the Hate Speech-Offensive task. On the RUHSOLD corpus, the same model achieved an accuracy of 0.95 and an F1 score of 0.94 for the Coarse-grained task, alongside an accuracy of 0.87 and an F1 score of 0.84 for the Fine-grained task. These results demonstrate the effectiveness of our hybrid approach for Roman Urdu hate speech detection.

Producción Científica

Waqar Ashiq mail , Samra Kanwal mail , Adnan Rafique mail , Muhammad Waqas mail , Tahir Khurshaid mail , Elizabeth Caro Montero mail elizabeth.caro@uneatlantico.es, Alicia Bustamante Alonso mail alicia.bustamante@uneatlantico.es, Imran Ashraf mail ,

Ashiq

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