Latest AI and machine learning research in medical education for healthcare professionals.
BACKGROUND/AIM: To determine the comparative efficacy of trained versus untrained generative artificial intelligence platforms in providing multiple-choice questions on traumatic dental injuries in a pediatric dentistry curriculum. MATERIAL AND METHODS: In this cross-sectional study, a standardized prompt was used on three generative artificial intelligence platforms, accessed via web interfaces i...
In this work, we introduce Progressive Growing of Patch Size (PGPS), an automatic curriculum learning approach for 3D medical image segmentation. Curriculum learning structures the training process by presenting progressively more complex samples to the model, often improving training convergence. In our case, we operationalize this by starting training with small patch sizes and gradually increas...
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...
We present the next generation of AMP, a neural network potential (NNP) with anisotropic message passing designed to study large biomolecular systems ...
Artificial intelligence (AI) is reshaping every stage of leukemia diagnostics, from digital morphology and multiparameter flow cytometry to next-gener...
BACKGROUND: As AI integration in medicine becomes critical, this study evaluated medical students' attitudes and knowledge regarding AI and determined...
Despite the obligation imposed by national and international accreditation standards to periodically verify reference intervals against local conditio...
OBJECTIVE: The American Board of Surgery In-Training Examination (ABSITE) assesses surgical resident knowledge, but manual analysis of program-wide da...
Advances in fetal diagnosis and therapy have created a need for clinicians with expertise spanning prenatal assessment and neonatal care. Current mate...
Artificial intelligence (AI) technologies are increasingly integrated into nursing education often framed as neutral tools that enhance learning effic...
The rapid integration of artificial intelligence into healthcare and education is transforming how nurses teach, learn and acquire knowledge. Despite ...
Variational autoencoders (VAEs) combined with neural ordinary differential equations provide a flexible framework for exploring neural latent-variable...
BACKGROUND: Traditional methods to practice patient interviewing skills for student pharmacists include the use of actors and role-playing. While effe...
This study introduces a simulation-based wearable biomechanical sensor network framework intended to support real-time fatigue monitoring and performa...
BACKGROUND: Artificial intelligence (AI) use is rapidly emerging in health care and health professions education; there is limited literature to guide...
BACKGROUND: Systematic collection of social determinants of health (SDoH) data remains inconsistent across healthcare settings, despite its critical i...
INTRODUCTION: The rapid integration of artificial intelligence (AI) technologies in healthcare, ranging from diagnostic tools to clinical decision sup...