Prevention

A biomechanical-constrained temporal learning framework for lightweight skeleton-based exercise recognition.

The recognition of exercises using skeletal pose sequences is a significant fitness technology, rehabilitation monitoring, and sports analytics. Nevertheless, the current practices tend to ignore the basic biomechanical processes of human motion. This paper presents a Biomechanical-Aware Temporal Learning (BATL), framework that incorporates human kinematic constraints and deep temporal model. The ...

Making Sense of Shoulder Exercise: Measuring the Accuracy of an Artificial Intelligence Model to Classify Shoulder Exercise via Wearable Sensors Among People With and Without Rotator Cuff Tendinopathy.

This study aimed to compare the accuracy of machine learning classification for three commonly prescribed shoulder exercises in people with and without rotator cuff tendinopathy. Eighteen participants with rotator cuff tendinopathy (mean age 54.2, SD 13.2; 50% female), followed by eighteen matched controls completed a laboratory-based shoulder strength testing protocol. Three exercises were perfor...

Effects of Different Exercise-Led Strategies on Mental, Nutritional, Physical and Cognitive Health in Community-Dwelling Older Adults: A Quasi-Experimental Study.

INTRODUCTION: Exercise interventions are widely used to promote physical and psychosocial health in community-dwelling older adults; however, the comp...

Research priorities for improved pandemic and epidemic intelligence.

Pandemic and epidemic intelligence integrates surveillance data with contextual knowledge to assess health risks and inform public health decisions. A...

A multimodal EMG and IMU dataset for assessing the quality of exercises designed for spatially constrained environments.

Regular physical training is essential for maintaining physical fitness in environments where exercise must be performed in limited space and without ...

An integrated wearable microfluidic electrochemical/colorimetric intelligent sensing platform for comprehensive sweat analysis.

Flexible wearable devices have attracted widespread attention in digital healthcare and personalized medicine driven by the growing demand for health ...

The effects of fatigue on the relation between ocular pursuit and interceptive performance in soccer experts.

Accuracy and duration of ocular pursuit of a target object have been linked to interceptive performance. Yet, previous assessments have not examined t...

Using artificial intelligence for physical exercise and healthy ageing among older adults: a scoping review.

Artificial Intelligence Applications across the Spectrum of Malnutrition: From Undernutrition to Obesity.

BACKGROUND: Malnutrition is a significant global public health challenge, with rising prevalence and vital consequences. Recent advances in artificial...

Medicinal and Edible Plants for the Management of Inflammatory Bowel Disease: Synergistic Modulation of the Microbiota-Metabolite-Immune Axis.

Inflammatory bowel disease (IBD) is a chronic condition driven by the intertwined interplay of gut dysbiosis, immune perturbation, and metabolic imbal...

Biomarker-anchored screening of dietary microplastics via a gut microbiota-informed machine learning model.

Microplastics (MPs) are increasingly recognized as emerging contaminants in the human diet, yet the absence of unified biomarker-anchored screening th...

Evaluation of the quality, reliability, and readability of ChatGPT-4 responses related to the treatment and rehabilitation of children with cerebral palsy.

UNLABELLED: This study aims to evaluate the reliability, quality, and readability of ChatGPT-4's responses to questions about cerebral palsy (CP) and ...

A covariate aware and dual convolutional network model for stadium crowd flow prediction.

Campus physical activities and sports facility utilization exhibit significant temporal fluctuations, which directly impact the efficiency of teaching...

Deep learning-based early prediction of carotid plaque response to lipid-lowering therapy using longitudinal multimodal ultrasound imaging.

OBJECTIVE: This study aimed to develop and validate a deep learning prediction model using longitudinal multimodal ultrasound imaging for early identi...

Proteomics for precision nutrition: current evidence and future directions.

PURPOSE OF REVIEW: This review critically evaluates proteomics research applied to clinical nutrition and metabolism published between mid-2024 and ea...

Oral microbiome signatures predict biological age and host health.

Identifying robust, non-invasive biomarkers of biological age is key to preventive medicine. While gut aging clocks exist, the oral microbiome remains...

Artificial intelligence in cancer survivorship: evaluating ChatGPT's performance in rehabilitation-related queries.

PURPOSE: This study aimed to evaluate the performance of ChatGPT in responding to patient-centered queries related to cancer rehabilitation. It examin...

The application of large language models in orthopedic postgraduate education: potentials, challenges, and future prospects.

With the widespread integration of artificial intelligence (AI), orthopedics postgraduate education is transitioning into the intelligent era. Large l...

Cardiopulmonary exercise testing before lung resection surgery: still indicated? Evaluating predictive utility using machine learning.

RATIONALE: Despite significant advances in patient care and outcomes, criteria for cardiopulmonary exercise testing (CPET) in risk stratification guid...

Establishment of prediction equations for available energy values of sorghum in broilers using machine learning and stepwise regression methods.

This study aimed to determine the available energy values of sorghum for Arbor Acres (AA) broilers and to develop and compare prediction equations usi...