Exercise & Fitness

Machine learning in bleeding risk assessment for low-molecular-weight heparin or fondaparinux: a predictive model study.

BACKGROUD:  No universally accepted model exists for predicting bleeding risk in patients receiving low-molecular-weight heparin or fondaparinux. OBJECTIVE:  This study leveraged seven machine learning algorithms to build a short-term bleeding risk prediction platform for this population. METHODS:  This retrospective real-world observational study included hospitalized patients who received low-mo...

Artificial intelligence denoising in cardiac photon-counting CT: mitigating BMI-related noise degradation while maintaining clinical interchangeability.

OBJECTIVES: To evaluate whether an artificial intelligence-based denoising (AID) algorithm can effectively attenuate body mass index (BMI)-related noise degradation in cardiac photon-counting detector CT (PCD-CT) while maintaining strict quantitative diagnostic equivalence and clinical interchangeability compared with quantum iterative reconstruction (QIR). MATERIALS AND METHODS: This retrospectiv...

Motion as Medicine: Harnessing the Power of Movement-Based Therapies.

Movement-based therapies use physical activity to alleviate pain, improve function, and enhance overall well-being. Evidence shows that regular moveme...

Use of Machine-Learning Models to Identify Clinical Features Associated With A Future Clinical Worsening Event in Patients With Pulmonary Arterial Hypertension.

Clinical worsening events are increasingly recognized as a meaningful outcome in pulmonary arterial hypertension (PAH). We applied machine-learning mo...

Regional disparities and metabolic determinants of type 2 diabetes in women aged 55 and older.

OBJECTIVE: To assess long-term trends, regional disparities, determinants, and quality of care for type 2 diabetes mellitus (T2DM) among women aged 55...

Learning Protein Representations with Conformational Dynamics.

MOTIVATION: Proteins change shape as they work, and these changing states control whether binding sites are exposed, signals are relayed, and catalysi...

Feasibility and Acceptability of a Prevention-Focused Screener for Perinatal Depression Risk: Mixed Methods Cohort Study.

BACKGROUND: More than 20% of perinatal women experience depression, with suicide being a leading cause of maternal death in the United States. Profess...

Machine learning-based prediction of ventilator therapeutic pressure for optimized CPAP titration.

BACKGROUND: Accurate prediction of therapeutic pressure for Continuous Positive Airway Pressure (CPAP) therapy is essential for effective treatment of...

Utilizing generative artificial intelligence to create simulated patient for history taking in gynecology.

INTRODUCTION: This study aimed to evaluate the effectiveness of a generative artificial intelligence based simulated patient model in improving gyneco...

How improper dataset split hinders model generalizability: a systematic comparison in Human activity recognition and exercise evaluation tasks.

BACKGROUND: Human Activity Recognition (HAR) and exercise assessment models are increasingly used in healthcare to support clinical evaluation, rehabi...

Practical guidance for echocardiography for cancer therapy-related cardiac dysfunction: 2026 focused update.

BACKGROUND: Cancer therapy-related cardiac dysfunction (CTRCD) has become an important clinical issue with advances in cancer treatment and improved p...

Contemporary heart failure evidence in 2025: a joint summary of key trials from the European Journal of Heart Failure and ESC Heart Failure Journal.

Heart failure (HF) remains a major global health challenge, characterized by high morbidity, mortality, and healthcare costs despite substantial advan...

Educating older adults to use technologies for health management in social settings: perspectives of older adults and community workers.

BACKGROUND: With the acceleration of global aging, the potential of digital technologies for self-care management among older adults has surged. Older...

Deep Learning-Based Comparison of Knee Minimum Joint Space Width in Patients with Rheumatoid Arthritis and Osteoarthritis Before Total Knee Arthroplasty.

OBJECTIVE: While osteoarthritis (OA) and rheumatoid arthritis (RA) can necessitate total knee arthroplasty (TKA), the mechanisms and radiographic patt...

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. Never...

Vision Transformer-Based Segmentation of Abdominal Subcutaneous and Visceral Fat on MRI.

The purpose of this study is to validate a deep learning-based vision transformer for automated quantification and segmentation of abdominal adipose t...

Psychological resilience as a selective perceptual amplifier in post-crisis learning: a dual-pathway model of academic motivation, perceived school support, and cognitive engagement - a multi-country study based on PISA 2022.

BACKGROUND: The global educational crisis triggered by the COVID-19 pandemic has posed persistent challenges to students' deep learning. Understanding...

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 withou...

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...