整合人工智能到医学教育的十二个实用技巧:教程来支持教育工作者在教学,研究,管理和道德领域
Alireza Jalali1, Kadidja Harbi Houssein1, Salomon Fotsing1
1Faculty of Medicine, University of Ottawa, Ottawa, ON, Canada.
JMIR medical education
|November 26, 2025
概括
这项研究为将人工智能 (AI) 整合到医学教育中提供了12个实用技巧. 这些以证据为基础的策略增强了教学,研究,管理和道德,为未来的临床医生准备技术驱动的医疗保健.
科学领域:
- 医疗教育 技术 技术 医学教育
- 医疗保健中的人工智能
- 数字学习环境 数字学习环境
背景情况:
- 人工智能 (AI) 正在改变医学教育.
- 有机会进行个性化学习,研究提升和行政简化.
- 有效的整合需要实际的,基于证据的指导.
研究的目的:
- 提供12个实用,基于证据的建议,用于将AI整合到医学教育中.
- 在教学,研究,管理和道德AI应用中指导教育工作者.
- 支持采用人工智能工具,以改善教育成果.
主要方法:
- 对教育当前人工智能应用的文献综述.
- 对人工智能整合现实世界的例子进行分析.
- 在关键领域为教育工作者提供策略的综合.
主要成果:
- 人工智能可以通过自适应平台和定制内容来个性化学习.
- 人工智能工具提供及时的反和人工智能生成的临床场景.
- 人工智能提高了研究效率 (文献评论,数据分析) 和手稿准备.
- 管理任务可以自动化,有助于战略规划和教师发展.
- 伦理地使用人工智能需要关注透明度,公平性和问责制.
结论:
- 实施这12个技巧使医学教育工作者能够利用AI.
- 人工智能集成提高了教育成果和效率.
- 医学教育必须适应,为人工智能驱动的医疗保健环境准备临床医生.
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