Primary Care

Exercise & Fitness

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

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Machine learning-guided acyl-ACP reductase engineering for improved in vivo fatty alcohol production.

Alcohol-forming fatty acyl reductases (FARs) catalyze the reduction of thioesters to alcohols and ar...

Explainable machine learning models of major crop traits from satellite-monitored continent-wide field trial data.

Four species of grass generate half of all human-consumed calories. However, abundant biological dat...

Artificial neural network and decision tree models of post-stroke depression at 3 months after stroke in patients with BMI ≥ 24.

OBJECTIVE: Previous studies have shown that excess weight (including obesity and overweight) can inc...

Feature Selection and Validation of a Machine Learning-Based Lower Limb Risk Assessment Tool: A Feasibility Study.

Early and self-identification of locomotive degradation facilitates us with awareness and motivation...

Predicting the Risk of Hypertension Based on Several Easy-to-Collect Risk Factors: A Machine Learning Method.

Hypertension is a widespread chronic disease. Risk prediction of hypertension is an intervention tha...

Skeletal muscle myostatin gene expression and sarcopenia in overweight and obese middle-aged and older adults.

BACKGROUND: Myostatin (MSTN) is a key negative regulator of muscle mass in humans and animals, havin...

Deep Integration of Physical Health Education Based on Intelligent Communication Technology.

In recent years, intelligent medical communication technology has developed rapidly, and the advance...

Evaluation of Teachers' Educational Technology Ability Based on Fuzzy Clustering Generalized Regression Neural Network.

The improvement of teachers' educational technology ability is one of the main methods to improve th...

Discrimination of vascular aging using the arterial pulse spectrum and machine-learning analysis.

Aging contributes to the progression of vascular dysfunction and is a major nonreversible risk facto...

Deep learning models for benign and malign ocular tumor growth estimation.

Relatively abundant availability of medical imaging data has provided significant support in the dev...

Model-based data augmentation for user-independent fatigue estimation.

OBJECTIVE: User-independent recognition of exercise-induced fatigue from wearable motion data is cha...

Robotic devices for paediatric rehabilitation: a review of design features.

Children with physical disabilities often have limited performance in daily activities, hindering th...

Intravenous Iron Replacement Improves Exercise Tolerance in COPD: A Single-Blind Randomized Trial.

INTRODUCTION: Iron deficiency affects exercise capacity because of the critical role iron plays in t...

Upper-Limb Motion Recognition Based on Hybrid Feature Selection: Algorithm Development and Validation.

BACKGROUND: For rehabilitation training systems, it is essential to automatically record and recogni...

Epistatic Net allows the sparse spectral regularization of deep neural networks for inferring fitness functions.

Despite recent advances in high-throughput combinatorial mutagenesis assays, the number of labeled s...

Deep learning multimodal fNIRS and EEG signals for bimanual grip force decoding.

Non-invasive brain-machine interfaces (BMIs) offer an alternative, safe and accessible way to intera...

Sociodemographic risk factors of under-five stunting in Bangladesh: Assessing the role of interactions using a machine learning method.

This paper aims to demonstrate the importance of studying interactions among various sociodemographi...

Informed training set design enables efficient machine learning-assisted directed protein evolution.

Directed evolution of proteins often involves a greedy optimization in which the mutation in the hig...

A machine learning approach to predict extreme inactivity in COPD patients using non-activity-related clinical data.

Facilitating the identification of extreme inactivity (EI) has the potential to improve morbidity an...

Recommendations for marathon runners: on the application of recommender systems and machine learning to support recreational marathon runners.

Every year millions of people, from all walks of life, spend months training to run a traditional ma...

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