人工智能辅助的共享决策培训,用于医学学生过渡到居住
Young-Min Kim1, Young-Mee Lee2, Do-Hwan Kim3
1Professor, Department of Emergency Medicine, and adjunct professor, Department of Medical Education, The Catholic University of Korea College of Medicine, Seoul, South Korea.
概括
在这项研究中,医学学生接受了人工智能 (AI) 辅助的共享决策 (SDM) 培训. 基于模拟的课程提高了学生对使用人工智能工具进行患者沟通和诊断的信心和理解.
科学领域:
- 医学教育 医学教育
- 医疗保健中的人工智能
- 临床决策支持 临床决策支持
背景情况:
- 临床实践越来越多地使用人工智能 (AI) 进行诊断,但医学教育缺乏将AI见解集成到诊断和共享决策 (SDM) 中的培训.
- 有效地使用人工智能生成的信息需要为临床医生提供专门的培训,以导航诊断辅助工具和患者沟通.
研究的目的:
- 开发和试点一个基于模拟的课程,以培训最后一年的医学学生在人工智能辅助的SDM.
- 评估课程对学生在SDM过程中利用AI工具的理解和信心的影响.
主要方法:
- 结合在线预学习和现场模拟的基于模拟的课程与最后一年的医学学生进行了模拟.
- 参与者使用了经过临床批准的AI工具 (Lunit INSIGHT CXR,MMG) 在模拟的患者遭遇中,专注于偶然发现和SDM.
- 该课程包括模拟患者反和专家辅导的对27名来自3所医学院的学生进行汇报.
主要成果:
- 在参与者对SDM和AI辅助SDM的理解和信心方面,观察到显著的改善 (P < .001).
- 学生报告说,人工智能工具促进了SDM和患者沟通,特别是通过视觉输出来支持诊断.
- 确定的局限性包括学生的知识差距和AI可解释性问题,并提出了课程整合的建议.
结论:
- 开发的课程有效地提高了医学学生在人工智能辅助SDM方面的技能.
- 建议将此类培训纳入正式课程,以更好地为未来的医生准备人工智能辅助的临床实践.
- 未来的努力应集中在将这种培训纳入体验式学习的本科或过渡课程中.
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