创新创业理论研究与实践 ›› 2025, Vol. 8 ›› Issue (16): 80-82.

• 教育改革与发展 • 上一篇    下一篇

人工智能辅助医学人才培养的探索与实践

王芳1, 彭喜涛2, 代玮1, 孙博1, 张家豪1   

  1. 1.郑州大学第一附属医院 河南郑州 450052;
    2.河南省直第三人民医院,河南郑州 450001
  • 出版日期:2025-08-25 发布日期:2025-11-18
  • 作者简介:王芳(1982—),女,河南驻马店人,博士研究生,主任医师,研究方向:生殖医学。
  • 基金资助:
    2024年河南省医学教育研究项目“人工智能辅助医学人才培养的探索与实践”(WJLX2024060)

Exploration and Practice of Artificial Intelligence-Assisted Medical Talent Cultivation

WANG Fang1, PENG Xitao2, DAI Wei1, SUN Bo1, ZHANG Jiahao1   

  1. 1. The First Affiliated Hospital of Zhengzhou University, Zhengzhou Henan, 450052, China;
    2. The Third People's Hospital of Henan Province, Zhengzhou Henan, 450001, China
  • Online:2025-08-25 Published:2025-11-18

摘要: 人工智能(AI)技术在医学教育中日益发挥重要作用,尤其是在应对知识更新迅速和医学生临床实践机会有限等问题方面。该文探讨了AI在医学教育中的多种应用,包括在线学习、智能辅导系统、虚拟现实(VR)模拟训练和个性化学习,能够帮助学生进行个性化学习,提升实践能力和临床思维。同时,该文将AI技术与医学课程结合,提出交叉学科培养模式,以应对未来医学领域的多样化需求;通过分析国内外成功案例,展示了AI辅助教学在提高学习成绩和临床技能方面的显著效果,为医学教育的创新与发展提供有益参考。

关键词: 人工智能, 医学教育, 医学人才培养, 个性化学习, 虚拟现实, 培养模式

Abstract: Artificial intelligence (AI) technology is gradually playing an important role in medical education, especially in addressing the issues of rapid knowledge updates and limited clinical practice opportunities. This article explores various applications of AI in medical education, including online learning, intelligent tutoring systems, virtual reality (VR) simulation training, and personalized learning, which can help students engage in personalized learning, enhance practical abilities, and clinical thinking. At the same time, the article discusses the integration of AI technology with medical courses and proposes an interdisciplinary training model to meet the diverse needs of the future medical field; By analyzing successful cases both domestically and internationally, the significant effects of AI assisted teaching in improving academic performance and clinical skills have been demonstrated, providing useful references for the innovation and development of medical education.

Key words: Artificial intelligence, Medical education, Medical talent training, Personalized learning, Virtual reality, Cultivation model

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