Latest AI and machine learning research in medical education for healthcare professionals.
The rapid advancement of personalized education has created an urgent need for intelligent learning path recommendation systems that can dynamically adapt to students' evolving knowledge states. However, existing learning path recommendation systems predominantly rely on static knowledge graphs or simple heuristic rules, failing to capture the temporal dynamics of student knowledge acquisition and...
Large language models (LLMs) are increasingly evaluated using medical examination datasets, yet most studies emphasize overall accuracy rather than the psychometric structure of test items. We evaluated five LLMs on 199 text-only cardiology residency in-service examination items previously characterized using resident-derived psychometric metrics. Three frontier models were compared with two open-...
BACKGROUND: The nursing process is a systematic, patient-centered framework essential for clinical reasoning and decision-making in nursing education....
In several simulation studies, long-term selection led to the rapid depletion of genetic variance. These outcomes differ from real-life observations t...
BACKGROUND: Curricular evaluation is core to nursing education and can benefit from artificial intelligence-based automation. Large language models of...
Wideband acoustic immittance (WAI) provides comprehensive frequency-dependent information for diagnosing middle ear pathologies. However, the scarcity...
BACKGROUND: Treatment selection between percutaneous coronary intervention (PCI) and coronary artery bypass grafting (CABG) for multi-vessel coronary ...
BACKGROUND: Anemia management in hemodialysis (HD) depends on individualized erythropoiesis-stimulating agent (ESA) dosing to achieve and maintain tar...
PURPOSE: The SMART (Stereotactic MR-Guided Adaptive Radiation Therapy) protocol for prostate SBRT has demonstrated favorable clinical outcomes using a...
INTRODUCTION: As ultrasound technology has become more advanced and accessible over the years, point-of-care ultrasound (POCUS) is becoming a tool as ...
Artificial intelligence (AI) and large language models are increasingly reshaping nephrology education. This review advances a hierarchical framework ...
PURPOSE: A wide range of methods exist for developing a clinical prediction model (CPM) and for performing variable selection. Our purpose was to deve...
BACKGROUND: To achieve a transition toward sustainable development, education is an essential driver of change. Factors like learners' attitudes, cult...
BACKGROUND: Interprofessional education (IPE) is essential for preparing health sciences students for collaborative practice, yet its implementation r...
OBJECTIVE: To conduct a preliminary single-center feasibility study of a YOLO-based deep-learning model for automated detection of lumbar disc herniat...
BACKGROUND/AIM: To determine the comparative efficacy of trained versus untrained generative artificial intelligence platforms in providing multiple-c...
BACKGROUND: The rapid integration of artificial intelligence (AI) and medical big data into health care is transforming diagnosis, treatment planning,...
PROBLEM: Inequities in educational infrastructure, faculty availability, and access to continuing professional development contribute to variability i...
BACKGROUND: Operating room (OR)-to-intensive care unit (ICU) handoffs are among the most complex and high-risk communication events in perioperative c...
PURPOSE: While the multidirectional optical bone densitometry approach, originally proposed based on simulation, has been previously reported, its exp...