Keywords
General practice
Resident physician
Standardized training
Application value
Submitted : 2025-06-11
Accepted : 2025-06-26
Published : 2025-07-11
Abstract
In the realm of medical education, the advancement of artificial intelligence (AI) technology has opened new opportunities for the standardized training of general medicine residents. This article focuses on the application of AI in this training, analyzing the current status and challenges of the training process. It explores the significance of AI in theoretical instruction, clinical practice, and assessment, while also considering the challenges and issues that arise from its use. The article proposes optimization strategies to enhance the quality of standardized training for general medicine residents, aiming to provide innovative insights and practical references.
References
Liu Z, Zhao J, Xi J, 2019, Experiences of Standardized Training for General Practitioners in Inner Mongolia. Continuing Medical Education, 33(8): 68–69.
Zhang Q, Zhong Y, Meng P, 2019, Problems and Thoughts on Standardized Training of General Practitioners in China. Chinese Post-Graduate Medical Education, 3(4): 369–379.
Wang Y, Zhao X, Yin A, 2019, Application and Evaluation of the Joint Stratified Teaching Method under the Mentor System in the Standardized Training of General Practitioners. Chinese Community Physicians, 35(33): 184–186.
Wang Y, Ding Z, Min H, et al., 2019, A Practical Exploration of the ‘Whole-Process Dual-Mentor System’ in the Standardized Training of General Practitioners. Clinical and Educational Practice of General Medicine, 34(12): 126–127.
Zhang Y, 2021, The Value of the ‘Internet+’ Model in the Management of Details of Standardized Training for Resident Physicians. Smart Health, 7(14): 182–184.
Li H, Wang X, 2020, Prospects and Challenges of the Application of Artificial Intelligence in Medical Education. Medical Education Management, 6(3): 201–205.
Zhang W, Chen J, 2021, Design and Application of an AI-Based Medical Simulation Teaching System. Chinese Digital Medicine, 16(5): 112–115.