一个考虑使用生成性AI用于健康的框架
Isabella Joy de Vere Hunt1,2, Kang-Xing Jin1,3, Eleni Linos4
1Stanford Center for Digital Health, Stanford University, Stanford, CA, USA.
NPJ digital medicine
|May 21, 2025
概括
这种观点为在医疗保健中使用生成人工智能 (GenAI) 提供了关键框架. 它概述了指导专业人士和政策制定者在伦理GenAI整合中的原则和风险.
科学领域:
- 医疗保健技术评估 医疗保健技术评估
- 医学中的人工智能
- 卫生政策和健康道德
背景情况:
- 生成型人工智能 (GenAI) 为医疗保健创新提供了重大机会.
- 由于GenAI的快速发展,需要对其评估和实施采取结构化的方法.
- 医疗保健专业人员和政策制定者需要关于负责任地采用这些技术的指导.
研究的目的:
- 在医疗保健环境中开发一个评估生成AI (GenAI) 的关键框架.
- 确定与GenAI集成相关的关键原则和潜在风险.
- 支持在医疗保健中对GenAI的伦理和有影响力的使用进行知情决策.
主要方法:
- 该框架是通过两次专家圆桌会议的见解来形成的.
- 与医疗保健专家进行了半结构面试.
- 对专家意见和发现的挑战进行了定性分析.
主要成果:
- 对GenAI评估的关键原则包括将应用程序映射到GenAI的优势,并建立严格的评估协议.
- 确定的风险包括数据隐私,算法偏见和需要强有力的验证.
- 会议强调了透明度,协作和持续监测的重要性.
结论:
- 结构化的评估框架对于将GenAI负责任地整合到医疗保健中至关重要.
- 解决伦理考虑和潜在风险对于成功采用GenAI至关重要.
- 这一观点为导航GenAI实施的医疗保健利益相关者提供了可行的指导.
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