BACKGROUND: Health recommender systems (HRSs) are digital platforms designed to deliver personalized health information, resources, and interventions tailored to users' specific needs. However, existing evaluations of HRSs largely focus on algorithmi...
OBJECTIVES: To evaluate provider-level variability across the full perioperative workflow using a computer vision-based artificial intelligence (AI) system that automatically detects and timestamps operating room events.
BACKGROUND: Multiple-choice questions (MCQs) are essential in medical education for assessing knowledge and clinical reasoning. Traditional MCQ development involves expert reviews and revisions, which can be time-consuming and subject to bias. Large ...
As artificial intelligence (AI) reshapes educational landscapes, ensuring ethical alignment and institutional responsiveness is essential particularly in skill-intensive sectors such as Technical and Vocational Education and Training (TVET). In this ...
BACKGROUND AND OBJECTIVES: The brain-predicted age difference (brain-PAD) is a novel marker of neurodegeneration in multiple sclerosis (MS). Brain-PAD has been associated with clinical disability in heterogeneous MS patient cohorts of varying ages an...
Machine learning (ML) is an artificial intelligence tool that focuses on learning by generating models using established algorithms that represent a given dataset. It can be used as a predictive tool for students' academic performance (AP) at both un...
BACKGROUND: Physical activity (PA) has emerged as a promising non-pharmacological intervention for pain management, the relationship between objectively measured PA patterns and multi-site pain remains poorly understood. This exploratory study invest...
BACKGROUND: Symptomatic knee osteoarthritis (KOA) imposes a substantial global health and economic burden. Although chronological age (CA) is a key risk factor, it poorly reflects interindividual aging heterogeneity. Biological age (BA), which is qua...
BACKGROUND: Digital technologies are reshaping health care, making digital health literacy (DHL) a critical competency for navigating online health information. Although widely conceived and measured as a unidimensional measure of DHL, the literature...
The purpose of this study was to develop a machine learning-based model using quantitative color fundus photography (CFP) data to predict myopia risk in school-age children, based on the axial length/corneal curvature radius (AL/CR) ratio, and to ide...
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