临床AI的飞行规则:从航空中吸取医学中人类-AI合作的经验教训
Ariel Yuhan Ong1,2,3, David A Merle4,5,6, Andreas Pollreisz7
1NIHR Moorfields Biomedical Research Centre, London, UK. ariel.ong@nhs.net.
NPJ digital medicine
|January 31, 2026
概括
医学中的人工智能 (AI) 提供了潜力,但也带来了风险. 从航空业的自动化旅程中学习,医疗领域应该将人工智能视为为更安全的患者护理的"数字副驾驶员".
科学领域:
- 医学技术 医学技术 医学技术
- 人与计算机的互动.
- 患者安全 患者安全
背景情况:
- 航空业从整合自动化中吸取了宝贵的教训,这提高了安全性,但引入了新的风险.
- 航空业早期的自动化导致过度依赖和不可预见的漏洞,需要强大的安全框架.
- 人工智能 (AI) 在临床环境中越来越多地被采用,反映了航空业的自动化轨迹.
研究的目的:
- 将航空自动化课程与AI在医学中的整合进行并行.
- 为医疗保健中安全有效地实施人工智能的框架提出建议.
- 在临床实践中倡导一个协作的人类-人工智能模型.
主要方法:
- 这种观点借鉴了临床医生和航空安全专家的经验.
- 它分析了航空业的历史数据和安全框架.
- 它提出了人工智能在医学中的感知和利用方式的概念转变.
主要成果:
- 将AI视为"数字副驾驶员"而不是"自动驾驶员"对于安全集成至关重要.
- 诸如基于场景的培训和临床医生比较等实际考虑是必不可少的.
- 维持核心临床技能需要最低限度的无辅助实践.
结论:
- 医疗界必须主动地从航空的自动化经验中学习,以确保患者的安全.
- 采用由特定培训和实践指南支持的人类-AI协作模式,将优化AI在医疗保健中的作用.
- 这种方法旨在通过有效利用人工智能,同时减轻其固有的风险来增强患者护理.
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