Primary Care

Exercise & Fitness

Latest AI and machine learning research in exercise & fitness for healthcare professionals.

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Robot-Assisted Approach to Diabetes Care Consultations: Enhancing Patient Engagement and Identifying Therapeutic Issues.

: Diabetes is a rapidly increasing global health challenge compounded by a critical shortage of diab...

Development and clinical evaluation of an AI-assisted respiratory state classification system for chest X-rays: A BMI-Specific approach.

PURPOSE: In this study, we aimed to develop and clinically evaluate an artificial intelligence (AI)-...

Machine learning modeling for predicting adherence to physical activity guideline.

This study aims to create predictive models for PA guidelines by using ML and examine the critical d...

Triboelectric Sensors Based on Glycerol/PVA Hydrogel and Deep Learning Algorithms for Neck Movement Monitoring.

Prolonged use of digital devices and sedentary lifestyles have led to an increase in the prevalence ...

Data Reconstruction Methods in Multi-Feature Fusion CNN Model for Enhanced Human Activity Recognition.

BACKGROUND: Human activity recognition (HAR) plays a pivotal role in digital healthcare, enabling ap...

Self-supervised machine learning methods for protein design improve sampling but not the identification of high-fitness variants.

Machine learning (ML) is changing the world of computational protein design, with data-driven method...

Predicting Type 2 diabetes onset age using machine learning: A case study in KSA.

The rising prevalence of Type 2 Diabetes (T2D) in Saudi Arabia presents significant healthcare chall...

Providing concentrate feed outside of the milking robot increases feed intake in dairy cows without reducing motivation to visit the robot.

Appropriate and adequate feeding is essential to maintaining good health, productivity and welfare o...

Comparison of time-to-event machine learning models in predicting biliary complication and mortality rate in liver transplant patients.

Post-Liver transplantation (LT) survival rates stagnate, with biliary complications (BC) as a major ...

Transfer Learning Prediction of Early Exposures and Genetic Risk Score on Adult Obesity in Two Minority Cohorts.

Due to ethnic heterogeneity in genetic architecture, genetic risk score (GRS) constructed within the...

Estimation of Hematocrit Volume Using Blood Glucose Concentration through Extreme Gradient Boosting Regressor Machine Learning Model.

Lifestyle diseases such as cardiovascular disorders, diabetes, etc. affect the physiological metabol...

Machine Learning Assisted-Intelligent Lactic Acid Monitoring in Sweat Supported by a Perspiration-Driven Self-Powered Sensor.

Lactic acid has aroused increasing attention due to its close association with serious diseases. A r...

Multi-modal dataset creation for federated learning with DICOM-structured reports.

Purpose Federated training is often challenging on heterogeneous datasets due to divergent data stor...

Information Extraction from Clinical Texts with Generative Pre-trained Transformer Models.

Processing and analyzing clinical texts are challenging due to its unstructured nature. This study ...

Application of Wearable Insole Sensors in In-Place Running: Estimating Lower Limb Load Using Machine Learning.

Musculoskeletal injuries induced by high-intensity and repetitive physical activities represent one ...

Cardiac Heterogeneity Prediction by Cardio-Neural Network Simulation.

The bidirectional interactions between brain and heart through autonomic nervous system is the prime...

Chaotic gradient based optimization with fuzzy temporal optimized CNN for heart failure prediction.

Heart failure is a leading cause of premature death, especially among individuals with a sedentary l...

The multiple uses of artificial intelligence in exercise programs: a narrative review.

BACKGROUND: Artificial intelligence is based on algorithms that enable machines to perform tasks and...

Machine learning web application for predicting varicose veins utilizing global prevalence data.

AimThis study aimed to develop a web-based machine learning (ML) model to predict the lifetime likel...

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