课程框架和人工智能的教育计划为医学学生,住院医生和执业医生:一个范围审查协议
Raymond Tolentino1, Ashkan Baradaran1, Genevieve Gore2
1Department of Family Medicine, McGill University, Montreal, QC, Canada.
JBI evidence synthesis
|July 12, 2023
概括
这份范围审查审查了人工智能 (AI) 课程框架和医疗专业人员的教育计划. 它旨在确定现有资源,并指导未来AI在医学教育发展.
科学领域:
- 医学教育 医学教育
- 人工智能的人工智能
- 课程开发 课程开发
背景情况:
- 医生需要对人工智能 (AI) 进行更深入的理解,以实现临床实践的整合.
- 医学教育课程必须纳入AI主题和概念.
- 课程框架对于指导医学人工智能教育至关重要.
研究的目的:
- 综合现有的AI课程框架和医疗专业人员教育计划的文献.
- 识别差距,并为未来AI在医学教育框架的发展提供信息.
主要方法:
- 根据JBI的方法进行范围审查.
- 在多个数据库 (MEDLINE,Embase,CENTRAL,CINAHL,Scopus) 和灰色文献中进行搜索.
- 从2000年起,包括英语和法语的文章,不包括会议摘要和会议记录.
主要成果:
- 从包含的物品中提取数据.
- 结果以表格形式呈现.
- 识别当前的AI课程框架和医学教育计划.
结论:
- 强调医疗培训中需要强大的AI教育框架.
- 为医生制定标准化的AI课程提供信息.
- 提高医疗保健专业人员在利用人工智能的能力.
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