Educational Technologies

Generative artificial intelligence driving the digital transformation of medical education: challenges and implementation pathways

  • Zhang Yuan ,
  • Wu Bohan ,
  • Tang Bin ,
  • Li Zhenglin ,
  • Yi Minhan
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  • 1Department of Respiratory Medicine, Xiangya Hospital, Central South University & National Clinical Research Center for Geriatric Disorders, Changsha 410008, China;
    2Department of Biomedical Informatics, School of Life Sciences, Central South University, Changsha 410013, China;
    3Department of Education, College of Education, Fujian Normal University, Fuzhou 350007, China

Received date: 2024-12-12

  Online published: 2025-09-28

Supported by

The Hunan Provincial Education Reform Project (HNJG-20230104); the Hunan Provincial Degree & Postgraduate Education Reform Project (2023JGYB026, 2023JGYB016, 2024JGYB042); the Undergraduate Education Reform Project of Central South University (2024jy103)

Abstract

Generative AI brings opportunities for advancing the digital transformation of medical education in areas such as handling highly abstract medical concepts, simulating clinical scenarios, and providing personalized medical teaching interactions. This article, based on the practical needs of digital transformation in medical education, analyzes the opportunities, risks, and implementation pathways of applying generative AI in medical education. It proposes a four-dimensional practical framework of ″literacy-resources-teaching-governance″ and emphasizes that the digital transformation of medical education empowered by generative AI must always adhere to the principle of ″physician-centeredness.″

Cite this article

Zhang Yuan , Wu Bohan , Tang Bin , Li Zhenglin , Yi Minhan . Generative artificial intelligence driving the digital transformation of medical education: challenges and implementation pathways[J]. Chinese Journal of Medical Education, 2025 , 45(10) : 754 -759 . DOI: 10.3760/cma.j.cn115259-20241212-01292

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