在医学课程中整合人工智能:方法和策略
Gheorghe Ioan Mihalas1, Coralia Cotoraci1, Casiana Boru1
1Vasile Goldis Western University Arad, Romania.
Studies in health technology and informatics
|August 8, 2025
概括
将医学人工智能 (AIM) 整合到医学教育中至关重要. 一个新的AIM课程揭示了学生在实际应用方面遇到了困难,强调了需要修订的课程,重点关注逻辑和快速工程.
科学领域:
- 医学教育 医学教育
- 医学中的人工智能 (AIM)
背景情况:
- 将AIM纳入医学课程是必不可少的,但具有挑战性.
- 将理论知识与实际应用相平衡是一个关键障碍.
研究的目的:
- 详细介绍医学学生AIM课程的开发,实施和评估.
- 确定挑战,并为未来的AIM课程设计提供见解.
主要方法:
- 课程开发与机构目标保持一致,并解决材料短缺问题.
- 实施涉及教学理论概念和实际应用.
- 评估重点是评估理论理解和实际应用之间的差距.
主要成果:
- 学生们展示了理解AIM理论和将其应用于医疗场景之间的差距.
- 存在学和自然语言处理 (NLP) 被确定为特别具有挑战性的领域.
- 课程的修订包括扩展了关于正规逻辑和提示工程的内容.
结论:
- 在AIM课程实施的第一年,为课程改进提供了宝贵的经验教训.
- 跨学科的合作对于成功地将AIM整合到医学教育中至关重要.
- 这种经验为准备未来医生有效利用新技术提供了路线图.
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