在医疗保健中适当实施和审查人工智能 (FAIR-AI) 的实际框架
Brian J Wells1, Hieu M Nguyen2, Andrew McWilliams3
1Department of Biostatistics and Data Science, Wake Forest University School of Medicine, Winston-Salem, NC, USA.
NPJ digital medicine
|August 12, 2025
概括
本研究引入了卫生系统评估和监测人工智能 (AI) 解决方案的实际框架,确保医疗机构的负责任创新和患者安全.
科学领域:
- 医疗信息学 医疗信息学
- 医疗人工智能 医疗人工智能
- 医疗保健管理的管理
背景情况:
- 卫生系统正在努力整合人工智能 (AI),同时保持安全和道德标准.
- 现有的AI评估框架缺乏对医疗保健环境的实际指导.
- 医疗保健中对人工智能的日益复杂和需求需要强有力的评估过程.
研究的目的:
- 为卫生系统制定规范性评估框架,以指导人工智能解决方案的实施.
- 为人工智能评估和监测提供实际资源,结构和标准.
- 解决目前在医疗保健中负责任地采用人工智能的框架中的差距.
主要方法:
- 进行了全面的文献审查.
- 与包括患者在内的关键利益相关者进行了深入采访.
- 一个多学科设计研讨会为框架开发提供了信息.
主要成果:
- 为卫生系统制定了规范性评估框架.
- 该框架概述了人工智能评估所需的资源,结构和标准.
- 提供模板文档,用于实施前后的AI监控.
结论:
- 开发的框架为实施人工智能的卫生系统提供了实际指导.
- 由于不断变化的AI环境,卫生系统应该将这个框架作为一个活着的文件来适应.
- 该框架支持负责任的创新和AI在医疗保健中的安全部署.
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