Exercise & Fitness

Development of an interpretable machine learning model for predicting stress urinary incontinence following the delivery of a first child.

INTRODUCTION: The goal of this research is to use machine learning (ML) techniques to create a risk prediction model for postpartum stress urinary incontinence (PSUI). To improve screening accuracy and optimize clinical care techniques, the goal is to determine the best model for clinical screening. METHODS: Telephone interviews and computerized medical records were used in this study to gather da...

Attitudes toward artificial intelligence tools in university students: associations with body appreciation and e-healthy diet literacy - implications for digital health education.

BACKGROUND: This cross-sectional study aimed to determine attitudes toward the use of artificial intelligence tools, body appreciation, and e-healthy diet literacy (e-HDL) levels among university students, and to analytically evaluate the relationships among these variables. METHODS: This cross-sectional study was conducted among 440 undergraduate university students aged 18-30 years enrolled at G...

Age-related determinants of geriatric depression: an analysis of theory-driven and data-driven approaches.

BACKGROUND: Geriatric depression is a prevalent mental health condition whose risk profile may vary across age strata. This study examined whether dep...

Application of AI-assisted PBL-CBL combined teaching in the diagnosis and treatment of post-herpetic neuralgia: a randomised controlled trial.

BACKGROUND: This study aimed to explore the efficacy of a teaching model integrating artificial intelligence-assisted problem-based learning (PBL) wit...

Effect of a sports-medicine-guided football program on physical fitness in adolescents: A controlled school-based trial.

Integrating artificial intelligence (AI) with sports medicine principles into school-based physical education may enhance physical fitness and reduce ...

Development of cognitive engagement and motivation using AI chatbot-facilitated questioning in medical education.

Artificial intelligence tools such as ChatGPT offer new opportunities to support medical students' learning through interactive questioning and instan...

Effectiveness of tele-rehabilitation using AI-guided exercise and pain neuroscience education for fibromyalgia (FIBROIA): Protocol for a randomized controlled trial.

INTRODUCTION: Fibromyalgia (FM) is a chronic condition characterized by widespread pain and cognitive dysfunction, with pharmacological treatments off...

Subgroup-Based Meta-Learning with Domain-Specific Self-Supervised Learning for Sarcopenia Detection from Musculoskeletal Ultrasound.

Sarcopenia is a progressive muscle disorder linked to aging, frailty, and increased healthcare burden. While ultrasound imaging offers a practical and...

Machine Learning Applications Within the Earlier Medicine Framework for Stroke: A Scoping Review.

This scoping review explores how machine learning (ML) has been applied to stroke research within the Earlier Medicine framework, which promotes proac...

Exploring User Trust and Adoption of AI Chatbots for Health and Fitness Management Across Age Groups.

This study investigates how individuals across different age groups use and perceive AI chatbots for health and fitness management. A quantitative sur...

Empirical Comparison of Causal Machine Learning and Post-Hoc AI Interpretability Models for Risk Factor Analysis: An Application to Medical Specialty Choice.

How medical students choose specialties shapes access to care. Prior work mostly describes patterns; newer prediction tools can rank influential facto...

Targeting metabolic dysregulation in postmenopausal breast cancer: Synergistic effects of nutrition-based interventions and exercise on molecular and cellular pathways.

Postmenopausal females diagnosed with breast cancer who are undergoing aromatase inhibitor (AI) therapy often exhibit metabolic disturbances, which ma...

Machine learning evaluation of TyG-based metrics for arteriosclerosis progression.

Insulin resistance (IR) is a significant risk factor for arteriosclerosis. The triglyceride-glucose (TyG) index and its obesity-related derivatives (T...

Gender disparities in random blood glucose levels among Pakistani adults with type 2 diabetes: a cross-sectional analysis.

This study investigated gender disparities in random blood glucose (RBS) levels among Pakistani adults with Type 2 Diabetes (T2D), examining biologica...

Gene expression integration and similarity score based modeling improve risk stratification in idiopathic venous thrombophilia.

BACKGROUND: Idiopathic venous thromboembolism (VTE) occurs in the absence of provoking factors, limiting the efficacy of current risk stratification. ...

Antibiotic therapy in febrile neutropenia in haematological patients: current considerations and future challenges.

The management of febrile neutropenia (FN) in oncohematological patients is undergoing a paradigm shift driven by a deeper understanding of patients' ...

Brain morphology in Anorexia Nervosa and its subtypes: A multi-cohort study of individual participant data.

BACKGROUND: In a recent coordinated meta-analysis of neuroimaging data, we reported gray matter (GM) alterations in acutely underweight patients with ...

Alignment Between Cardiologists and AI-Driven Diagnostic Systems: Mixed Methods Study.

BACKGROUND: The clinical value of artificial intelligence (AI)-based diagnostic systems depends not only on their accuracy but also on how well their ...

Deep learning-based motion correction: cardiac motion artifact and image quality improvements on chest CT.

PURPOSE: Since the clinical application of computed tomography (CT), cardiac and respiratory motion artifacts have caused decreased image quality and ...

Applications of bioimpedance measurement in clinical and allied fields: a comprehensive review.

BACKGROUND: Accurate and timely disease detection is essential in modern healthcare. Conventional imaging methods such as computed tomography (CT), ma...