中国卒中杂志 ›› 2025, Vol. 20 ›› Issue (3): 380-383.DOI: 10.3969/j.issn.1673-5765.2025.03.017

• 教学园地 • 上一篇    

人工智能在提升神经科住院医师脑血管病诊治能力中的应用与挑战

张淋源,沈翔,吕海燕,王国栋,吴云成   

  1. 上海 200080 上海交通大学医学院附属第一人民医院神经内科
  • 收稿日期:2024-03-01 出版日期:2025-03-20 发布日期:2025-03-20
  • 通讯作者: 吴云成 yunchw@medmail.com.cn
  • 基金资助:
    上海市2021年度“科技创新行动计划”自然科学基金项目(21ZR1451700)
    上海市第一人民医院临床创新研究团队课题(CCTR-2022B07)

The Application and Challenges of Artificial Intelligence in Enhancing the Diagnosis and Treatment Capabilities of Neurology Residents in Cerebrovascular Diseases

ZHANG Linyuan, SHEN Xiang, LYU Haiyan, WANG Guodong, WU Yuncheng   

  1. Department of Neurology, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200080, China
  • Received:2024-03-01 Online:2025-03-20 Published:2025-03-20
  • Contact: WU Yuncheng, E-mail: yunchw@medmail.com.cn

摘要: 近年来,人工智能(artificial intelligence,AI)的发展为神经科住院医师培训提供了新的技术支持。脑血管病是神经科学中应用AI最早、最成熟的领域之一,将AI有机融入传统的神经科住院医师培训中,有助于夯实神经科基本功、优化神经影像分析、辅助疾病个体化诊疗,从而加速青年医师的成长,对我国脑血管病的防治体系建设大有裨益。然而,AI的应用目前也面临着诸多挑战,如医师对AI过度依赖、“AI幻觉”、AI技术的局限和伦理问题等。本文系统总结了AI在住院医师脑血管病培训中的综合应用和价值,探讨潜在风险与挑战,并提出优化AI应用的策略,以期为未来AI技术在医学教育中的深度融合提供有益参考。

文章导读: 本文系统探讨了人工智能在神经科住院医师脑血管病培训中的应用价值、潜在风险及优化策略,旨在为人工智能与医学教育的深度融合提供参考。

关键词: 住院医师规范化培训; 神经病学; 脑血管病; 人工智能

Abstract: In recent years, the development of artificial intelligence (AI) has provided new technological support for the training of neurology residents. Cerebrovascular disease is one of the earliest and most mature fields of AI application in neuroscience. Integrating AI organically into traditional neurology resident training can help consolidate neurology basic skills, optimize neuroimaging analysis, and assist in individualized diagnosis and treatment of disease, thereby accelerating the growth of young physicians and greatly benefiting the construction of the prevention and treatment system for cerebrovascular disease in China. However, the application of AI in medical training also presents challenges, including physicians’ over-reliance on AI, “AI hallucinations”, limitations of AI technology, and ethical concerns. This article systematically summarizes the comprehensive application and value of AI in the training of residents in cerebrovascular disease, explores potential risks and challenges, and proposes strategies to optimize AI applications, aiming to provide valuable references for the deep integration of AI in medical education in the future.

Key words: Standardized residency training; Neurology; Cerebrovascular disease; Artificial intelligence

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