Advancements in artificial intelligence transforming medical education: a comprehensive overview

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Publicat a:	Medical Education Online vol. 30, no. 1 (Dec 2025)
Autor principal:	Khakpaki, Aliasghar
Publicat:	Taylor & Francis Ltd.
Matèries:	Educational technology Ethics Databases Medical education Computer assisted instruction > CAI Resistance Technological change Education Clinical skills Search strategies Medical schools Learning processes Adoption of innovations Infrastructure Artificial intelligence Resource allocation Innovations Ethical dilemmas Case studies Privacy Learning Customization Training Professional education Teaching Health services College faculty Empathy Decision making Teaching methods Health care Medical decision making Educational objectives Clinical decision making Learning outcomes Medical screening Skill development
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Resum:	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 like faculty resistance and technological infrastructure gaps, limit broader adoption. Conclusion: AI is an important tool in medical education, offering significant opportunities to enhance learning outcomes and bridge educational gaps. However, its successful integration requires ethical frameworks, faculty training, and equitable resource allocation. A balanced approach that combines technological innovation with human-centered pedagogy is essential to preserve empathy and ethical care in healthcare.
ISSN:	1087-2981
DOI:	10.1080/10872981.2025.2542807
Font:	Sociology Database