保持病床教学:一个由人工智能支持的系统,用于捕捉自发的临床教学
Rugved Parmar1, Daoud Eldawud1, Nischal Sharma1
1SUNY Downstate Health Sciences University, Brooklyn, NY, USA.
Rounds Copilot是一个人工智能工具,可以捕捉床边教学,将口头内容转换为结构化的学习材料,如教学点和评估问题. 这一创新保留了临床体验中宝贵的教育时刻.
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
背景情况:
- 床边轮回提供独特的自发教学机会.
- 目前捕捉床边教学的方法是不够的,导致失去了学习的时刻.
- 学习者面临的挑战是在患者护理期间实时记录教学.
研究的目的:
- 开发一种由人工智能支持的系统,Rounds Copilot,用于自动捕捉和结构化床边教学.
- 转换自发的口语教学在轮到可用的学习材料.
- 提高临床教学内容的保存和可访问性.
主要方法:
- 开发了Rounds Copilot,这是一个整合语音转录和自然语言处理的AI系统.
- 该系统自动提取教学点,对其进行分类 (证据与珍珠),并生成评估问题.
- 使用模拟的15分钟的教学体验进行初始处理.
主要成果:
- 该系统在不到三分钟的时间内处理了一个模拟的遭遇,生成了七个教学内核和五个多选题.
- 证据分类有助于学习者优先考虑信息,评估问题有助于知识巩固.
- 非正式居民反强调了证据与珍珠区分和评估问题的有用性.
结论:
- 循环Copilot有效地将动态的床边教学转化为结构化,可访问的学习资源.
- 该系统提供了一种具有成本效益和用户友好的解决方案,以保护临床教育.
- 未来的工作将集中在现实世界的验证和临床部署途径上.
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