Exercise & Fitness

Research priorities for data science and artificial intelligence in global health: an international consensus exercise.

Applications of data science and artificial intelligence (AI) in global health are expanding, yet research remains fragmented and often misaligned with the needs of low-income and middle-income countries (LMICs). To address this misalignment, we conducted a global research priority-setting exercise using the Child Health and Nutrition Research Initiative (CHNRI) method. 155 research ideas were sco...

Advancing Personalized Strategies for Obesity Prevention Through Biologically and Behaviorally Tailored Interventions: The Strategic Framework for the BETTER4U Initiative.

The BETTER4U project (Preventing Obesity through Biologically and bEhaviorally Tailored inTERventions for You) is a Horizon Europe initiative (GAP 101080117) dedicated to advancing our understanding of the multifaceted etiology of obesity. The project aims to move beyond current knowledge of obesity-related determinants by examining the system-level interactions between biological (including genet...

Decoding Naturalistic Episodic Memory with Artificial Intelligence and Brain-Machine Interface.

Episodic memory integrates what, where, and when of experience into a coherent autobiographical narrative. Decades of research have identified hippoca...

Increase in knee-adjacent subcutaneous fat is associated with cartilage degeneration independent of BMI: A four-year analysis of the OAI dataset.

OBJECTIVE: To determine whether changes in knee-adjacent subcutaneous fat (kaSCF) are associated with changes in cartilage thickness, cartilage T2 rel...

Predicting non-alcoholic fatty liver disease (NAFLD) using machine learning algorithms: Evidence from a large-scale community cohort in Taiwan.

Closely associated with metabolic disorders, non-alcoholic fatty liver disease (NAFLD) substantially increases the risk of hepatocellular carcinoma. T...

The regional landscape of the human colon culturome in health and cystic fibrosis.

UNLABELLED: Cystic fibrosis (CF) alters gut physiology, yet its impact on microbial communities across colonic regions (ascending, transverse, descend...

Distinguishing post-COVID from long-COVID in adults: Development and validation of a biomarker signature using targeted proteomics and machine learning in a cross-sectional observational study.

BACKGROUND: COVID-19 can have diverse clinical manifestations, ranging from asymptomatic infection to critical illness with multiorgan involvement. Wh...

Disabilities and Generative Artificial Intelligence Education in Rheumatology Fellowship: Educational Module and Simulation Exercise.

OBJECTIVE: People with rheumatic and musculoskeletal diseases (RMDs) can acquire disabilities that affect their participation in work and school. Gene...

Multi-dimensional dynamic monitoring of gut microbiota-emotion axis and precision exercise intervention in compulsory drug rehabilitation: A 24-week randomized controlled trial.

BACKGROUND/OBJECTIVES: Substance use disorders (SUDs) present a global health challenge with high relapse rates. Emerging evidence implicates gut micr...

Predicting aerobic granular sludge structural instability: An intelligent early-warning framework integrating convolutional neural network and fluorescence fingerprint features.

Aerobic granular sludge (AGS) was recognized as an innovative alternative superior to activated sludge processes, yet its development has been constra...

For machine learning to advance precision pain medicine, we must exercise caution.

Task-evoked brain network dynamics underlying cognitive control using source-localized EEG and machine learning.

OBJECTIVE: Functional connectivity (FC) coordinates brain activity during cognitive tasks, yet the influence of demographic variables and health facto...

Using machine learning to identify the strongest personal, school, and family correlates of youth mental health and well-being.

Research has identified numerous personal, school, and family factors associated with youth mental health, yet it remains unclear which correlates bes...

Smartphone App Using Reinforcement Learning for Obesity: Single-Arm Feasibility Study.

BACKGROUND: While behavioral interventions remain an evidence-based treatment for obesity, they often require long durations and frequent sessions. To...

Artificial intelligence-based clustering to identify functional risk phenotypes in heart failure.

BACKGROUND: Patients with heart failure (HF) frequently suffer from undetected declines in cardiorespiratory fitness (CRF), which significantly increa...

Ryanodine receptor 2 mutations in catecholaminergic polymorphic ventricular tachycardia: From molecular mechanisms to precision medicine.

Catecholaminergic polymorphic ventricular tachycardia is a classic example of the successful transfer of genetic cardiology from gene discovery to imp...

Anatomic Features of the Abdomen Predict Donor Site Complications in Deep Inferior Epigastric Artery Perforator Flap Breast Reconstruction: A Machine Learning Approach.

BACKGROUND: Abdominal donor site complications remain significant concerns in Deep Inferior Epigastric Perforator (DIEP) flap breast reconstruction. I...

GlucoseGo: a simple tool to predict hypoglycaemia during exercise in type 1 diabetes.

AIMS/HYPOTHESIS: This study aimed to develop an accessible tool, derived using machine learning, to predict hypoglycaemia risk at the start of exercis...

Machine learning derived proliferating T cell-related signature: a novel biomarker for prognosis and treatment efficacy in clear cell renal cell carcinoma.

BACKGROUND: Clear cell renal cell carcinoma (ccRCC) exhibits profound molecular heterogeneity, and reliable biomarkers for predicting clinical outcome...

Non-pharmacological treatment of AECOPD.

Acute exacerbations of chronic obstructive pulmonary disease (AECOPDs) are acute events characterized by rapid worsening of dyspnea, cough, and sputum...