Exercise & Fitness

Motion capture dataset of 137 post-operative total hip replacement patients performing activities of daily living.

Three-dimensional motion capture is a powerful tool in clinical and engineering applications, but it can be time consuming, expensive, and difficult to access patient populations. Here, we present an open-access dataset comprising 3D motion capture and ground reaction force data from 137 post-operative total hip replacement patients performing eight activities of daily living (ADLs): normal walkin...

Integrated prognostic evaluation of TyG and TyG-BMI in critically ill patients with comorbid atrial fibrillation and ischemic stroke using machine learning.

The effect of artificial intelligence-supported applications on critical thinking motivation and clinical decision making in nursing students: path analysis.

BACKGROUND: Artificial intelligence (AI)-supported applications are increasingly integrated into nursing education and have the potential to influence...

Smartphone Detection of Fetal Movements Using Artificial Intelligence.

OBJECTIVE: To evaluate whether machine learning could be used with audio recordings from a smartphone to detect fetal movements that create disruption...

Task complexity and AI dependency among college students: the mediating roles of cognitive load, future anxiety, and task motivation.

PURPOSE: This study aims to clarify the associations between task complexity and Artificial Intelligence (AI) dependency among university students and...

In vivo quantification of arterial active mechanics using deep learning-assisted pressure-area analysis.

Active arterial mechanics, governed by vascular smooth muscle contraction, are critical to physiological regulation, cardiovascular disease progressio...

AI-Driven Analysis of Cardiopulmonary Exercise Tests to Identify Gas Exchange and Ventilatory Thresholds.

BACKGROUND: A cardiopulmonary exercise test (CPET) provides the estimated lactate threshold (θLT) and respiratory compensation point (RCP) through vis...

Assessment of socioeconomic and demographic risk factors for low birth weight using model-agnostic explainable ensembles.

BACKGROUND AND OBJECTIVE: Low birth weight (LBW) is a major global public health concern, strongly linked to neonatal morbidity and long-term health c...

Maternal Gut Microbiome as a Predictor of Insulin Therapy Requirement in Gestational Diabetes.

BACKGROUND: Gestational diabetes mellitus (GDM) often requires pharmacological intervention beyond lifestyle modification to achieve optimal glycemic ...

Peak Oxygen Uptake Prediction From Resting and Submaximal Variables of Cardiopulmonary Exercise Testing.

BACKGROUND: Cardiorespiratory fitness, as measured by peak oxygen uptake during cardiopulmonary exercise testing, is a prognostic indicator. We aim to...

Contribution of social determinants to symptoms of generalized anxiety disorder.

Symptoms of anxiety are known to be triggered by a range of life context factors including early life trauma, poor sleep quality, infrequent exercise,...

Pipeline-optimized machine learning for chronic fatigue syndrome diagnosis: A lightweight, interpretable model using blood biochemical and metabolomic data.

INTRODUCTION AND BACKGROUND: Chronic fatigue syndrome (CFS) is a debilitating multisystem disorder with persistent fatigue and functional impairment, ...

Beyond BMI: Deep Learning Segmentation-Driven CT Reveals Body Composition Changes After Metabolic and Bariatric Surgery.

BACKGROUND: Body mass index (BMI) is the primary metric used to evaluate metabolic and bariatric surgery (MBS) outcomes but does not distinguish tissu...

XNet: Enhancing Physical Activity Intensity Assessment With Attentional Multidomain Fusion and Visual Analytics.

Sedentary behavior (SB) is a major global health concern, necessitating accurate physical activity (PA) intensity monitoring. Conventional machine-lea...

Influence of body composition on the efficacy of nivolumab plus ipilimumab for metastatic clear cell renal cell carcinoma.

BACKGROUND: Immune checkpoint inhibitor therapy (ICI) with nivolumab+ipilimumab is a first-line (1L) standard for metastatic clear cell renal cell car...

Sleep quality prediction in basketball athletes using a deep learning framework with an attention mechanism based on multimodal data.

It is difficult for traditional prediction methods to comprehensively evaluate the sleep quality problems of college basketball players, which is a ke...

Predicting metabolic syndrome risk in Chinese adults using integrated features of movement behaviors and dietary intake: a machine learning approach.

BACKGROUND: China is undergoing a rapid nutritional and epidemiological transition. Traditional epidemiological approaches often examine diet and phys...

Machine Learning for Estimating Cardiorespiratory Fitness in Patients With Obesity: Protocol for a Retrospective and Prospective Multicenter Cohort Study.

BACKGROUND: Cardiorespiratory fitness (CRF) is a key predictor of cardiovascular and other health-related diseases in individuals with obesity. CRF is...

Predicting Non-Response to Multicomponent Treatment in Fibromyalgia: Development and Validation of a Machine Learning Model.

BACKGROUND: Multicomponent programs combining therapeutic exercise, cognitive-behavioral therapy, and pain neuroscience education demonstrate overall ...

Potent efficacy of an NA-targeting antibody against a broad spectrum of H5N1 influenza viruses.

For nearly 30 years, Goose/Guangdong-derived highly pathogenic avian influenza H5N1 viruses have posed significant risks to economic stability, food s...