走向负责任的未来:人工智能支持临床决策支持的建议
Steven Labkoff1,2, Bilikis Oladimeji3, Joseph Kannry4
1Quantori, Boston, MA 02142, United States.
Journal of the American Medical Informatics Association : JAMIA
|September 26, 2024
概括
医疗保健中的人工智能 (AI) 需要为安全可靠的临床决策支持 (CDS) 系统提供强大的框架. 建议包括验证,监测和培训,以确保负责任的AI集成.
科学领域:
- 医疗信息学 医疗信息学
- 医疗保健中的人工智能
背景情况:
- 将AI整合到医疗保健中为临床决策提供了重大潜力.
- 关键的挑战包括确保AI可信度,减轻偏见,并保持患者安全.
- 人工智能工具评估的标准化方法缺乏,这阻碍了部署前和后的有效评估.
研究的目的:
- 为AI在临床决策支持系统 (CDS) 中的安全和有效开发,测试,监督和使用提出实际方法,规则和指导方针.
- 解决在医疗实践中对人工智能支持的CDS可靠应用的挑战.
主要方法:
- 一个工作组,由伯特以色列牧师医疗中心临床信息学部门和美国医学信息学协会共同赞助,于2023年5月召开会议.
- 建立共识涉及网络研讨会和2023年9月为期两天的研讨会,与200多名行业利益相关者.
- 用定性分析和为期4个月的代共识过程来确定挑战并提出解决方案.
主要成果:
- 主要建议侧重于建立安全可靠的AI-CDS系统.
- 开发强大的验证,验证和认证流程至关重要.
- 建立国家一级的安全监测和报告机制,以及最终用户培训是必不可少的.
结论:
- 对于支持人工智能的CDS,需要一个全面的框架,强调可信度,透明度和安全性.
- 这一框架必须涵盖模型培训,可解释性,验证,认证,监测和持续评估.
- 负责任的AI整合需要集体利益相关者的努力,强有力的安全措施和持续的创新,未来的步骤包括试点信任机制和建立最佳实践.
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