人工智能如何用于FDA授权的医疗器械:在1016个授权中进行分类
Rohan Singh1, Monika Bapna2, Abdul Rahman Diab1
1Dana-Farber Cancer Institute, Boston, MA, USA.
NPJ digital medicine
|July 2, 2025
概括
对1016个支持AI/ML的医疗设备的审查创造了一个新的分类学. 该分类系统跟踪医疗保健中的人工智能 (AI) 和机器学习 (ML) 应用,并注意到设备开发的趋势.
科学领域:
- 医疗技术 医疗技术 医学技术
- 医疗保健中的人工智能
- 监管科学 监管科学
背景情况:
- 人工智能和机器学习 (AI/ML) 的快速进步导致了AI/ML支持的医疗设备的激增.
- 对于研究人员,监管机构和临床医生来说,了解这些设备的风景至关重要.
- 现有的分类可能无法完全捕捉AI/ML在医疗应用中的功能细微差别.
研究的目的:
- 开发一个全面的分类系统来分类由美国食品和药物管理局 (FDA) 授权的支持AI/ML的医疗设备.
- 识别和分析这些设备的关键临床和AI相关特征.
- 建立一个框架来跟踪AI/ML应用在医疗器械中的演变.
主要方法:
- 对1016个FDA授权的AI/ML支持的医疗器械进行系统审查.
- 基于临床应用和AI/ML功能开发一种新的分类学.
- 对设备特征和应用趋势的定量分析.
主要成果:
- 定量图像分析是最普遍的AI/ML应用,尽管随着时间的推移,其比例有所下降.
- 超过100个设备使用AI用于数据生成目的.
- 目前没有被审查的设备使用大型语言模型 (LLM).
结论:
- 开发的分类学提供了当前在FDA授权的医疗器械中AI/ML使用的清晰概述.
- 这种分类系统是监测该领域未来进步和趋势的基本工具.
- 这些发现凸显了AI/ML在医学中的应用的不断变化的性质,迄今为止,基于LLM的设备显著缺失.
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