Exercise & Fitness

Health Prediction Using Hybrid Deep Learning Models: A Transparent and Interpretable Approach.

Obesity has become alarming globally, with mounting health emergencies related to a number of chronic conditions like cardiovascular disease, diabetes, and metabolic disorders. Despite growing global awareness, accurately categorising obesity remains challenging due to its multifactorial nature involving genetic, lifestyle, environmental, and psychological determinants. Traditional methods based o...

Predicting minimal clinically important difference after hip arthroscopy: logistic regression versus machine learning.

PURPOSE: Hip arthroscopy outcomes for femoroacetabular impingement (FAI) remain heterogeneous, with 30-40% of patients failing to achieve meaningful improvement. We aimed to develop and validate a predictive model for achievement of minimal clinically important difference (MCID) using routine preoperative variables, and to compare logistic regression with machine learning algorithms. METHODS: We r...

Assessing predictive accuracy of 2D digital templating in fluoroscopy-guided direct anterior approach total hip arthroplasty.

INTRODUCTION: Preoperative 2D digital templating aids surgical planning in total hip arthroplasty (THA). We evaluated template accuracy by comparing p...

A Gamified Pain Management Intervention for Adults With Chronic Pain in Mainland China: Single-Arm Pre-Post Pilot Study With Machine Learning Predictive Modeling.

BACKGROUND: The widespread prevalence of chronic pain (CP) significantly impacts daily functioning worldwide. In mainland China, maintaining engagemen...

Large-scale AI analysis reveals missed opportunities in albuminuria testing and disease-modifying therapy implementation.

BACKGROUND: Albuminuria is a key diagnostic and prognostic biomarker of chronic kidney disease (CKD), associated with adverse cardiovascular and renal...

Beyond Weight: Systems Biology and Precision Medicine Redefine Obesity as a Multidimensional Disease.

BACKGROUND: Traditional weight-centered models do not fully capture the biological complexity of obesity. Systems biology offers a new framework by in...

Effects of a ChatGPT-generated eccentric training programme on speed, change of direction, agility, and jumping performance in U14 tennis players: A non-randomised controlled study.

This non-randomised controlled-trial aimed to examine the effects of a ChatGPT-generated eccentric training (ET) programme, which was subsequently val...

Patch Uniform Fusion Transformer with circle-inspired optimized walrus-based feature selection for high-dimensional data analysis.

PURPOSE: Feature selection approaches have historically been limited by processing performance during high-dimensional data analysis, which presents a...

A novel predictive model for evaluating thrombus regression in postpartum venous thromboembolism patients.

INTRODUCTION: Antithrombotic evaluation of postpartum venous thromboembolism (VTE) after anticoagulant therapy is challenging because of the lack of h...

Preparing Physicians for Tomorrow's Practice: Contemporary Practice Competencies as a Framework for Technology-Driven Change.

Medical education has long relied on stable, high-level program objectives to articulate the outcomes of undergraduate medical training. These objecti...

Integrating Machine Learning into Fracture Liaison Services: Toward precision risk stratification in osteoporosis care: A prospective cohort study.

BACKGROUND: Traditional fracture risk assessment tools have limitations in accurately predicting re-fracture risk. Machine learning (ML) approaches of...

Apply machine learning to predict greenhouse gas emissions in aerobic composting and achieve emission reduction by nanomembrane covering mode.

Previous studies have utilized nanomembranes to reduce greenhouse gas (GHG) emissions in composting. However, few studies have explored their effectiv...

Integrated Strategies for Nursing and Rehabilitation in Lung Cancer Patients.

This review delineates the pivotal role of nursing and rehabilitation in perioperative management and chemotherapy support for lung cancer patients, w...

Artificial Intelligence-Enabled Prediction of Reversible Versus Irreversible Chemotherapy-Induced Myocardial Injury: Toward Precision Cardio-Oncology.

Cancer therapy-related cardiac dysfunction remains a major cause of morbidity among cancer survivors and may interrupt life-saving oncologic therapy o...

HybridMolGen: A Unified Framework for Goal-Directed Molecular Generation via Multi-Objective Reinforcement Learning.

MOTIVATION: De novo molecular design remains a fundamental challenge in drug discovery, requiring simultaneous optimization of multiple conflicting ob...

Using Machine Learning to Design Effective Antimicrobial Dosing Regimens.

Resistant bacterial infections remain a major clinical challenge, often necessitating combination therapy, namely use of two or more antibiotics with ...

Prediction of post-COVID chronic fatigue syndrome using data mining and machine learning techniques in Isfahan COVID cohort study.

BACKGROUND: Post-COVID Fatigue (PCF) is one of the most common issues people face after recovering from COVID-19. Due to the heterogeneity of clinical...

A novel machine learning model of smartphone-based 1-minute sit-to-stand test for prediction of six-minute walk test distance in patients with COPD.

BACKGROUND: Regular assessment of exercise tolerance is essential for managing COPD, nevertheless, the standard 6-Minute Walk Test (6MWT) is difficult...

From statistics to deep learning in single-molecule fluorescence resonance energy transfer analysis.

Single-molecule fluorescence resonance energy transfer (smFRET) is a versatile technique for studying biomolecular dynamics and function by detecting ...

Central Obesity Measured by Weight-Adjusted Waist Index Is Associated With Lean MASLD.

BACKGROUND: In individuals with normal body weight, altered fat distribution contributes to metabolic dysfunction and hepatic steatosis. We hypothesiz...