The increasing application of generative artificial intelligence large language models (LLMs) in various fields, including medical education, raises questions about their accuracy. The primary aim of our study was to undertake a detailed comparative ...
BACKGROUND: The American Society of Clinical Nutrition recommends 37 to 44 h of undergraduate medical nutrition education. The Total Health Curriculum at Geisinger Commonwealth School of Medicine (GCSOM) contains 14 h of objective-based nutritional i...
BACKGROUND: Healthcare simulation is critical for medical education, with traditional methods using simulated patients (SPs). Recent advances in artificial intelligence (AI) offer new possibilities with AI-based simulators, introducing limitless oppo...
Academic medicine : journal of the Association of American Medical Colleges
39705530
The rapid advancement of generative artificial intelligence (GAI) is poised to revolutionize medical education, clinical decision-making, and health care workflow. Despite considerable interest and a surfeit of newly available tools, medical educator...
OBJECTIVES: Artificial intelligence (AI) is rapidly being integrated into medical imaging practice, prompting calls to enhance AI education in undergraduate radiography programs. Combining evidence from literature, practitioner insights, and industry...
INTRODUCTION: Artificial intelligence has permeated all aspects of our existence, and medical imaging has shown the burgeoning use of artificial intelligence in clinical environments. However, there are limited empirical studies on radiography studen...
BACKGROUND: Reflection fosters self-regulated learning by enabling learners to critically evaluate their performance, identify gaps, and make plans to improve. Feedback, in turn, provides external insights that complement reflection, helping learners...
BACKGROUND: Artificial intelligence (AI) is set to shape the future of medical practice. The perspective and understanding of medical students are critical for guiding the development of educational curricula and training.
BACKGROUND: Medical students often struggle to engage with and retain complex pharmacology topics during their preclinical education. Traditional teaching methods can lead to passive learning and poor long-term retention of critical concepts.
Advances in artificial intelligence (AI) are overtaking the progress in teaching and assessment. Traditional assignments, such as written reports and posters, have become obsolete as these can be created almost entirely using AI tools. As educators,...