Advancements in artificial intelligence transforming medical education: a comprehensive overview
Abstract
Background: Artificial intelligence (AI) is revolutionizing medical education by introducing innovative tools and reshaping traditional teaching and learning methods. AI technologies such as virtual and augmented reality, adaptive learning platforms, and AI-driven assessments are increasingly recognized for their potential to enhance diagnostic precision, clinical decision-making, and personalized learning experiences.
Objective: This narrative review explores the current trends, challenges, and innovations associated with the integration of AI in medical education. It aims to critically examine how AI transforms teaching and learning processes while addressing ethical concerns and practical barriers.
Methods: We performed a systematic literature search across three major databases (PubMed, Scopus, and Web of Science) for publications dated 2010-2024. Our search strategy employed key terms including 'artificial intelligence,' 'medical education,' and 'AI-based learning platforms' to identify relevant peer-reviewed articles, review papers, and case studies. After screening and selection, 67 studies met our inclusion criteria for final analysis.
Results: AII technologies improve learning outcomes by creating personalized, immersive, and interactive environments. They support clinical decision-making and procedural skills training while addressing diverse learner needs. However, ethical issues like data privacy, algorithmic biases, and equitable access, coupled with challenges…
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Evidence Hub reads this as a systematic review, done in people. Its evidence level is 1 of 5 (Highest · pooled evidence). Pooled evidence from several studies sits at the top of the evidence pyramid.
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