Exercise & Fitness

Stress or Arousal? Exercise Confounding in Wearable Stress Detection.

Wearable stress-detection models are commonly validated by separating rest from stress, but this does not establish that their outputs are specific to stress rather than broader physiological activation. We re-analysed two public wearable datasets and made a matched within-dataset stress-specificity experiment the primary test. PhysioNet event tags were used to reconstruct protocol-defined rest an...

AI vs. human touch: Comparing non-AI and AI-mediated informal digital learning of English (IDLE) and their associations with affective variables and L2 willingness to communicate.

The advancement of digital technologies has spurred a surge in research on informal digital learning of English (IDLE) in second language (L2) acquisition. However, few studies have compared the relationships between artificial intelligence (AI) and non-AI-IDLE on affective variables such as grit, motivation, self-confidence, and L2 speaking anxiety, which are associated with L2 willingness to com...

Atherosclerosis prediction with large language models via prompt engineering.

Atherosclerosis remains difficult to detect in its early stages due to its often asymptomatic nature. While artificial intelligence, particularly Larg...

Secondary fragility fractures after hip fracture surgery in four thousand, four hundred and eighteen older adults: risk factors and internal validation of an interpretable machine-learning model.

BACKGROUND: Secondary fragility fractures remain a major complication after hip fracture surgery in older adults, yet individualized postoperative ris...

Global transitions of concomitant patterns and risk factors of cardio-renal-metabolic conditions among the elderly.

BACKGROUND: Cardio-renal-metabolic (CRM) diseases-including ischemic heart disease (IHD), stroke, type 2 diabetes (T2DM), and chronic kidney disease (...

A protocol for validation of novel artificial intelligence-based framework for dyspnoea investigation with cardiopulmonary exercise testing.

BACKGROUND: Exertional dyspnoea largely represents the sensory translation of an ever-growing dynamic mismatch between ventilatory demand and capacity...

Cancer risk and mortality assessment in the overweight population: evaluation of single and integrated models based on inflammatory markers.

BACKGROUND: Chronic inflammation is a significant driver of carcinogenesis, particularly in the context of obesity; yet its role and the predictive va...

Dementia Carers' Perspectives on Paper- and Artificial Intelligence (AI)-Based Assessment Tools: A Qualitative Think-Aloud Study Using the COM-B Framework.

ObjectivesCarer observations provide valuable longitudinal and contextual information for dementia assessment, but traditional informant-based questio...

Improving 10-year cardiovascular disease risk prediction using automated machine learning.

AIMS: To develop a cardiovascular disease (CVD) risk prediction model with improved accuracy and interpretability by integrating diverse risk factors ...

Heterogeneous effects of preoperative beta blockers on 30-day mortality after coronary artery bypass surgery.

BACKGROUND: The role of preoperative β-blocker therapy in patients with ventricular dysfunction undergoing coronary artery bypass grafting (CABG) rema...

A comparative evaluation of ChatGPT-assisted and traditional methods of teaching diagnostic assessments to medical students: A randomized controlled study.

The rapid development of artificial intelligence (AI) technology has brought new opportunities and challenges to the ever-evolving field of medical ed...

The Health Benefits of Exercise: Molecular and Cellular Mechanisms.

Exercise is a low-cost lifestyle intervention that can prevent and alleviate various diseases. It is a potent physiological stimulus that activates co...

Unsupervised machine learning with Cluster Analysis in patients with rheumatoid arthritis: insights in CV risk phenotypes from a multicentre Italian cohort.

Rheumatoid arthritis (RA) patients face increased cardiovascular (CV) risk, yet existing 10-year estimation tools often underperform. This study evalu...

User Engagement and Feature Preferences in an AI-Powered mHealth Intervention for Diabetes Prevention: Secondary Analysis of a Randomized Controlled Trial.

BACKGROUND: Prediabetes is highly prevalent and increasing globally, yet lifestyle interventions remain underused. AI-driven mobile health (mHealth) t...

The future of precision oncology and artificial intelligence in Belgium: scenarios and policy responses.

PURPOSE: Precision medicine, also known as personalized medicine, enables the provision of tailored health services to patients. In the prevention, ea...

Gene-level complexity explains genome-wide variation in the distribution of fitness effects.

The distribution of fitness effects (DFE)-describing how harmful, neutral, or beneficial new mutations are-is central to understanding how populations...

Use of artificial intelligence in the peer review process of sports and exercise medicine research.

Visual prompt engineering for multimodal and irregularly sampled medical data.

BACKGROUND: A patient undergoes multiple examinations in each hospital stay, where each provides different facets of the health status. These assessme...

Machine learning models for early detection of urinary tract infections in kidney transplant patients.

BACKGROUND: Renal transplantation is the preferred treatment for end-stage chronic kidney disease but requires lifelong immunosuppression, increasing ...

Trusting the Algorithm or Trusting the Nurse? Critical Care Nurses' Experiences of Automation Bias and Professional Autonomy in AI-Assisted Early Warning.

BACKGROUND: Artificial intelligence-assisted early warning systems (AI-EWS) are increasingly integrated into critical care, yet little is known about ...