算法旅程图:在医疗保健中实施AI解决方案的切实方法
William Boag1, Alifia Hasan1, Jee Young Kim1
1Duke Institute for Health Innovation, Durham, NC, USA.
NPJ digital medicine
|April 9, 2024
概括
这项研究绘制了在医疗保健中开发和实施SepsisWatch AI工具的过程. 它为克服AI/ML采用障碍和在算法系统中运行道德原则提供了经验教训.
科学领域:
- 医疗信息学 医疗信息学
- 人工智能在医学中的应用
- 临床决策支持系统 临床决策支持系统
背景情况:
- 将AI/ML整合到医疗保健中,由于复杂的用户-技术交互,会带来挑战.
- 缺乏理解阻碍了AI/ML的采用和AI解决方案的最佳实践的开发.
研究的目的:
- 在医疗保健系统中记录AI解决方案的完整生命周期,SepsisWatch.
- 确定可通用的见解,以克服AI/ML在医疗保健中的采用障碍.
- 为医疗保健人工智能系统运行道德原则提供最佳实践信息.
主要方法:
- 与参与SepsisWatch项目的工程师和科学家进行了20次采访.
- 开发了一个"算法旅程地图",详细介绍了社会和技术活动.
- 记录了人工智能解决方案的采购,开发,集成和生命周期管理.
主要成果:
- "算法旅程图"提供了对人工智能解决方案生命周期的全面概述.
- 确定了关键的"经验教训",包括建模假设,利益相关者参与和组织结构.
- 突出了可概括的见解,用于识别和导航医疗保健中的AI/ML采用障碍.
结论:
- 该研究为了解和管理医疗保健中的AI/ML集成提供了实际框架.
- 调查结果有助于开发可持续和道德的人工智能实施的最佳实践.
- "算法旅程地图"是采用人工智能解决方案的医疗机构的一个有价值的工具.
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