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Exercise & Fitness

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

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Harnessing AI to revolutionize photocatalytic degradation of Tetracycline via optimized UV/ZrO/NaOCl reaction pathways.

This paper assesses the presentation of Gradient Boosting Regression (GBR), Ridge Regression (RR), a...

R-CKGAT: a recommendation algorithm based on scientific fitness knowledge graph.

In recent years, with the spread and popularization of health knowledge, more and more people have b...

Predictive factors of hypoglycemia in type 2 diabetes: a prospective study using machine learning.

Hypoglycemia is a serious complication in individuals with type 2 diabetes mellitus. Identifying who...

Predicting cardiovascular risk with hybrid ensemble learning and explainable AI.

Cardiovascular diseases (CVDs) are still one of the leading causes of death globally, underscoring t...

Clinical Efficacy of Multimodal Exercise Telerehabilitation Based on AI for Chronic Nonspecific Low Back Pain: Randomized Controlled Trial.

BACKGROUND: Exercise therapy is strongly recommended as a treatment for chronic nonspecific low back...

Cell-Free Protein Synthesis as a Method to Rapidly Screen Machine Learning-Generated Protease Variants.

Machine learning (ML) tools have revolutionized protein structure prediction, engineering, and desig...

Sociodemographic Profile of People with Diagnosed Pancreatic Cancer in the UK: Retrospective Sentinel Network Cohort Study.

Pancreatic cancer is a devasting disease which is an increasing cause of cancer mortality. The aim o...

A validated multivariable machine learning model to predict cardio-kidney risk in diabetic kidney disease.

BACKGROUND: Individuals with diabetic kidney disease (DKD) often suffer cardiac and kidney events. W...

Machine learning-assisted prediction and identification of key factors affecting nitrogen metabolism for aerobic granular sludge.

To achieve higher denitrification efficiency with reduced energy consumption in aerobic granular slu...

A metaheuristic optimization-based approach for accurate prediction and classification of knee osteoarthritis.

Knee osteoarthritis (KOA) is a severe arthrodial joint condition with significant global socioeconom...

EM-PLA: Environment-aware Heterogeneous Graph-based Multimodal Protein-Ligand Binding Affinity Prediction.

MOTIVATION: Predicting protein-ligand binding affinity accurately and quickly is a major challenge i...

Application of Artificial Intelligence in Cardio-Oncology Imaging for Cancer Therapy-Related Cardiovascular Toxicity: Systematic Review.

BACKGROUND: Artificial intelligence (AI) is a revolutionary tool yet to be fully integrated into sev...

Early Detection and Remote Care of Frailty for Older Adults Living in Sparsely Populated Rural Areas in Hokkaido, Japan: A Case Study.

The global increase in the number of older people aged 65 and over is causing concern in healthcare ...

Distributed Representations for Cognitive Control in Frontal Medial Cortex.

In natural and artificial neural networks, modularity and distributed structure afford complementary...

Predicting Body Fat Percentage from Simple Anthropometric Measurements: A Machine Learning Approach.

Accurately assessing body fat percentage (BF%) is crucial for healthcare and fitness but is hindered...

Exploring the Impact of PA and Sedentary Behavior on Gout Risk in Hyperuricemia: Insights From Machine Learning and SHAP Analysis.

BACKGROUND: Individuals with hyperuricemia (HUA) are widely recognized as being at increased risk fo...

Applications, challenges and future directions of artificial intelligence in cardio-oncology.

BACKGROUND: The management of cardiotoxicity related to cancer therapies has emerged as a significan...

Predicting Fitness-Related Traits Using Gene Expression and Machine Learning.

Evolution by natural selection occurs at its most basic through the change in frequencies of alleles...

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