人工智能能力:当前状态和挑战
Sian Tsuei1,2
1Department of Family Practice, University of British Columbia , David Strangway Bldg, 5950 University Blvd 3rd Floor, Vancouver, BC, V6T 1Z3, Canada, + 1 604-822-5431.
JMIR medical education
|March 11, 2026
概括
随着人工智能 (AI) 的发展,医学教育需要新的能力,专注于选择合适的AI工具,而不仅仅是优化它们的使用. 这项研究提出了一个框架,以指导医生对人工智能能力的发展.
科学领域:
- 医学教育 医学教育
- 人工智能的人工智能
- 医疗信息学 医疗信息学
背景情况:
- 人工智能 (AI) 的快速发展需要为医疗专业人员定义新的能力.
- 目前的重点是优化AI输出和理解技术/规范性考虑,但这可能会产生减少的回报.
- 在选择合适的人工智能工具方面,向能力的转变显得至关重要.
研究的目的:
- 总结医疗教育当前的人工智能能力领域.
- 引入人工智能能力发展的层次框架.
- 识别开发和测量人工智能能力的挑战.
主要方法:
- 审查医疗教育中现有的AI能力领域.
- 提出一个层次框架:认知 (理解),操作 (使用) 和元AI (选择) 领域.
- 讨论基于能力的医学教育和AI绩效指标开发的挑战.
主要成果:
- 目前的人工智能能力发展需要进一步的综合.
- 提出的层次框架包括认知能力,操作能力和超级AI能力.
- 挑战包括定义有意义的能力,特定环境的测量和开发绩效指标.
结论:
- 专注于选择人工智能工具的新能力对于医学教育至关重要.
- 拟议的框架可以指导人工智能能力发展的优先设定.
- 解决测量和指标开发方面的挑战对于成功将人工智能整合到医疗保健中至关重要.
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