Medical Education Management ›› 2026, Vol. 12 ›› Issue (4): 496-502.doi: 10.3969/j.issn.2096-045X.2026.04.010

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Realistic challenges and practical pathways of generative artificial intelligence–empowered medical student training

  

  1. 1. School of Marxism, Capital Medical University, Beijing 100069, China; 2. School of Basic Medicine, Capital Medical University, Beijing 100069, China; 3. Operating Room, Chengde County Hospital of Traditional Chinese Medicine, Chengde 067400, China
  • Received:2025-06-04 Revised:2026-03-19 Accepted:2026-04-13 Online:2026-08-20 Published:2026-09-01

Abstract:

In response to the transformation of diagnosis and treatment models brought about by artificial intelligence technologies in the healthcare sector, and to meet the practical demand of the Healthy China initiative for medical talents adapted to digital and intelligent development, this paper focuses on issues related to generative artificial intelligence (GenAI)-empowered medical student training and conducts research on the practical challenges and implementation pathways faced by medical student education. The findings suggest that GenAI-empowered medical student training still faces three major challenges: barriers to its introduction into medical schools, insufficient development and application of the advanced capabilities of GenAI, and the risk of misleading information in its use. Accordingly, this paper proposes three innovative pathways: fully leveraging GenAI's advantages to support teaching assistance; deepening the application of GenAI to empower research training and clinical education; and regulating GenAI usage to prevent technology-induced misinformation risks. This study aims to provide practical reference for the cultivation of interdisciplinary medical talents in digitally and intelligently evolving clinical environments.