专家对人工智能能力能力清单和医学学生评估框架的共识 (2025年版)
Meng-Chun Gong1, Hui Pan2, Hui Liu3
1Guangdong Medical University,Dongguan,Guangdong 523808,China.
概括
这一共识概述了人工智能 (AI) 识字能力清单和医学学生的评估框架. 它旨在为未来的医疗保健专业人员为人工智能驱动的医疗环境做好准备.
科学领域:
- 医疗教育 医学教育
- 医疗保健中的人工智能
- 基于能力的教育 基于能力的教育
背景情况:
- 智能医疗的快速发展需要培训医疗专业人员以AI识字.
- 现有的医学教育框架需要适应,以整合人工智能能力.
- 基于能力的医学教育 (CBME) 为开发AI准备的临床医生提供了基础.
研究的目的:
- 为医学学生制定一个全面的AI识字能力清单.
- 建立一个实际的评估框架,用于评估医疗教育中的AI能力.
- 引导医学院将人工智能纳入其智能医疗保健课程.
主要方法:
- 一个双轮的Delphi方法,涉及一个多学科专家小组.
- 系统的文献审查,以告知能力发展.
- 能力模型和Miller临床能力金字塔的整合.
主要成果:
- 一个21指标的人工智能识字能力名单为医学学生,分为知识 (8),技能 (8),和态度 (5).
- 一个拟议的评估系统,包括标准化测试,情境判断测试和基于AI场景的客观结构化临床检查.
- 在入院,临床前和临床培训阶段推的一种纵向评估策略.
结论:
- 开发的AI能力清单和评估框架具有科学严谨性和实际适用性.
- 这种共识是医学院将人工智能纳入教育的关键参考.
- 它支持为智能医疗时代培养复合医疗人才.
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