Primary Care

Exercise & Fitness

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

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Application of Additive Manufacturing and Deep Learning in Exercise State Discrimination.

With the rapid development of sports technology, smart wearable devices play a crucial role in athle...

The impact of preschool children's physical fitness evaluation under self organizing maps neural network.

To improve the scientific accuracy and precision of children's physical fitness evaluations, this st...

Polymer Biodegradation in Aquatic Environments: A Machine Learning Model Informed by Meta-Analysis of Structure-Biodegradation Relationships.

Polymers are widely produced and contribute significantly to environmental pollution due to their lo...

Fuzzy Synchronization Likelihood Graph in Deep Neural Networks for Human Motion Time Series Analysis.

Variable interactivity is crucial in biological multivariate time series analysis. This research sug...

A Fusion Network With Stacked Denoise Autoencoder and Meta Learning for Lateral Walking Gait Phase Recognition and Multi-Step-Ahead Prediction.

Lateral walking gait phase recognition and prediction are the premise of hip exoskeleton application...

Development and validation of a new nomogram for self-reported OA based on machine learning: a cross-sectional study.

Developing a new diagnostic prediction model for osteoarthritis (OA) to assess the likelihood of ind...

AI and Uncertain Motivation: Hidden allies that impact EFL argumentative essays using the Toulmin Model.

This study investigates the combined impact of artificial intelligence (AI) tools and Uncertain Moti...

Optimizing Kernel Extreme Learning Machine based on a Enhanced Adaptive Whale Optimization Algorithm for classification task.

Data classification is an important research direction in machine learning. In order to effectively ...

Exercise improves body composition, physical fitness, and blood levels of C-peptide and IGF-1 in 11- to 12-year-old boys with obesity.

INTRODUCTION: Exercise is vital in preventing and treating obesity. Despite its importance, the unde...

Utilising causal inference methods to estimate effects and strategise interventions in observational health data.

Randomised controlled trials (RCTs) are the gold standard for evaluating health interventions but of...

Digital phenotyping from heart rate dynamics: Identification of zero-poles models with data-driven evolutionary learning.

Heart rate response to physical activity is widely investigated in clinical and training practice, a...

Machine learning prediction model of the treatment response in schizophrenia reveals the importance of metabolic and subjective characteristics.

Predicting early treatment response in schizophrenia is pivotal for selecting the best therapeutic a...

A comprehensive and bias-free machine learning approach for risk prediction of preeclampsia with severe features in a nulliparous study cohort.

Preeclampsia is one of the leading causes of maternal morbidity, with consequences during and after ...

Breath Analyzer for Real-Time Exercise Fat Burning Prediction: Oral and Alveolar Breath Insights with CNN.

The increasing prevalence of obesity and metabolic disorders has created a significant demand for pe...

Machine learning analysis of factors affecting college students' academic performance.

This study aims to explore various key factors influencing the academic performance of college stude...

Optimizing hypertension prediction using ensemble learning approaches.

Hypertension (HTN) prediction is critical for effective preventive healthcare strategies. This study...

Development of a Virtual Robot Rehabilitation Training System for Children with Cerebral Palsy: An Observational Study.

This paper presents the development of a robotic system for the rehabilitation and quality of life i...

Core reference ontology for individualized exercise prescription.

"Exercise is medicine" emphasizes personalized prescriptions for better efficacy. Current guidelines...

Prediction of talent selection in elite male youth soccer across 7 seasons: A machine-learning approach.

This study aimed to investigate the relative importance of parameters from several domains associate...

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