美国医疗成像AI/ML设备的监管考虑:概念和挑战
Nicholas Petrick1, Weijie Chen1, Jana G Delfino1
1U.S. Food and Drug Administration, Center for Devices and Radiological Health, Office of Science and Engineering Labs, Silver Spring, Maryland, United States.
Journal of medical imaging (Bellingham, Wash.)
|June 26, 2023
概括
本指南向人工智能和机器学习 (AI/ML) 开发人员介绍美国食品和药物管理局 (FDA) 的医疗器械法规. 它涵盖了AI/ML设备提交,数据考虑和安全和创新的医疗技术的监管挑战.
科学领域:
- 医疗器械监管法规 医疗器械监管法规
- 医疗保健中的人工智能
- 机器学习用于医学成像.
背景情况:
- 人工智能和机器学习 (AI / ML) 技术越来越多地集成到医疗成像设备中.
- 在医疗保健中AI/ML的快速发展带来了独特的监管障碍.
- 开发人员需要指导,以导航AI/ML医疗设备的监管途径.
研究的目的:
- 让开发人员熟悉AI/ML医疗设备的监管环境.
- 概述AI/ML设备的数据考虑和提交流程.
- 讨论当前的监管挑战和与医学中AI/ML相关的持续活动.
主要方法:
- 介绍美国食品和药物管理局 (FDA) 的监管概念和流程.
- 解释各种医学成像AI/ML设备类型的基本评估.
- 对AI/ML设备提交的信息和测试要求的概述.
主要成果:
- 人工智能/ML设备的分类和监管途径取决于风险,技术和预期用途.
- 提交的关键组成部分包括模型描述,数据,非临床和多读者多病例测试.
- 美国食品和药物管理局积极参与制定指导方针,促进良好的机器学习实践,并评估现实世界的性能.
结论:
- 美国食品和药物管理局的AI/ML计划旨在确保患者获得安全有效的设备.
- 监管工作支持患者安全和医疗AI/ML创新的进步.
- 持续参与监管研究和透明度对于AI/ML医疗器械开发至关重要.
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