为临床医生提供人工智能教育
Tim Schubert1,2,3, Tim Oosterlinck1,4, Robert D Stevens5
1Department of Applied Mathematics and Theoretical Physics, University of Cambridge, Cambridge, UK.
医疗人工智能 (AI) 需要临床医生教育才能安全有效地使用. 这项研究提出了一个分层框架,以指导医学教育利益相关者制定人工智能课程,以改善患者的治疗结果.
科学领域:
- 医学教育 医学教育
- 医疗保健中的人工智能
- 临床实践中的临床实践
背景情况:
- 医疗人工智能的快速发展需要临床医师培训.
- 确保人工智能工具的安全和有效使用对于患者的治疗结果至关重要.
- 现有的医学教育框架可能无法充分解决人工智能集成问题.
研究的目的:
- 为医疗人工智能专业知识提出一个分层框架.
- 概述医学培训不同阶段的教育挑战.
- 为医学AI课程开发提供建议.
主要方法:
- 概念框架的发展.
- 分析人工智能集成中的教育挑战.
- 医学教育中最佳实践的审查.
主要成果:
- 提出了医疗人工智能专业知识的三层模型.
- 确定了各级医学教育面临的具体挑战.
- 为课程设计提供了可适应的建议.
结论:
- 对医疗人工智能教育的结构化方法是必不可少的.
- 利益相关者可以利用拟议的框架来定制课程.
- 积极的教育策略将加强人工智能采用和患者护理.
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