在临床和运营工作流程中运行可靠的人工智能
1HCA Healthcare, Nashville, TN, United States.
Frontiers in digital health
|March 2, 2026
概括
医疗保健中的可靠的人工智能 (AI) 不仅需要技术验证;它来自社会技术系统. 这个框架通过工作流程设计,治理和持续评估来实现人工智能信任,以确保安全部署.
科学领域:
- 医疗信息学 医疗信息学
- 人工智能的人工智能
- 临床决策支持系统 临床决策支持系统
背景情况:
- 人工智能 (AI) 在医疗保健中越来越多地用于决策和运营效率.
- 尽管取得了进展,但现实世界的人工智能采用受到利益相关者之间信任问题的限制.
- 当前值得信赖的AI框架侧重于技术和道德原则,缺乏操作指导.
研究的目的:
- 提出一个全面的框架,用于在医疗保健中运行可靠的人工智能.
- 将重点从以模型为中心的验证转移到社会技术系统设计.
- 为安全,公平和可持续的AI部署提供务实的基础.
主要方法:
- 将人工智能可信度视为社会技术系统的新兴属性.
- 开发一个框架,整合以决策为中心的设计和人类-人工智能角色划分.
- 整合故障可见性,嵌入式问责制和纵向性能监测.
主要成果:
- 可信度是作为系统级属性而构成的,而不仅仅是模型属性.
- 拟议的框架通过工作流集成,使可信的人工智能变得可操作.
- 关键组成部分包括明确的角色定义,透明的故障分析和持续的绩效跟踪.
结论:
- 实施可信的人工智能需要一种社会技术方法,而不仅仅是技术解决方案.
- 该框架为安全地将AI整合到临床和运营工作流程中提供了实际指导.
- 持续评估和强有力的治理对于在医疗保健中持续影响人工智能至关重要.
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