浙江大学, 中国食品药品检定研究院, 海军军医大学第二附属医院. 人工智能医疗器械性能评价通用方法专家共识(2023)[J]. 协和医学杂志, 2023, 14(3): 494-503. DOI: 10.12290/xhyxzz.2023-0137
引用本文: 浙江大学, 中国食品药品检定研究院, 海军军医大学第二附属医院. 人工智能医疗器械性能评价通用方法专家共识(2023)[J]. 协和医学杂志, 2023, 14(3): 494-503. DOI: 10.12290/xhyxzz.2023-0137
Zhejiang University, National Institutes for Food and Drug Control, Shanghai Changzheng Hospital. Expert Consensus on General Methods for Performance Evaluation of Artificial Intelligence Medical Devices (2023)[J]. Medical Journal of Peking Union Medical College Hospital, 2023, 14(3): 494-503. DOI: 10.12290/xhyxzz.2023-0137
Citation: Zhejiang University, National Institutes for Food and Drug Control, Shanghai Changzheng Hospital. Expert Consensus on General Methods for Performance Evaluation of Artificial Intelligence Medical Devices (2023)[J]. Medical Journal of Peking Union Medical College Hospital, 2023, 14(3): 494-503. DOI: 10.12290/xhyxzz.2023-0137

人工智能医疗器械性能评价通用方法专家共识(2023)

Expert Consensus on General Methods for Performance Evaluation of Artificial Intelligence Medical Devices (2023)

  • 摘要: 人工智能(artificial intelligence, AI)医疗器械的研发与转化进入活跃期, 产品的性能评价方法需要标准化且亟待创新。以促进行业发展、支撑监管、提升人工智能医疗器械产品质量为目标, 浙江大学牵头联合中国食品药品检定研究院等多家专业机构, 依托人工智能医疗器械标准化技术归口单位, 分析了人工智能医疗器械性能评价的共性问题, 对相关测试方法进行了梳理总结。本文在专家组共识的基础上, 对各种测试方法及其应用进行具体介绍, 同时对相关的测试数据抽样加以阐述, 以期在业内形成统一认识, 从而促进人工智能医疗器械性能评价方法与流程的标准化, 为人工智能医疗器械的高质量发展保驾护航。

     

    Abstract: Artificial intelligence medical devices are rapidly evolving, and the performance evaluation methods of the products need to be standardized and innovated. With the goal of promoting industry, supporting supervision, and improving the quality of artificial intelligence medical device products, Zhejiang University, in cooperation with a number of professional institutions such as the National Institutes for Food and Drug Control, and relying on the centralized unit of artificial intelligence medical device standardization technology, led the efforts to analyze the common problems in performance evaluation and summarize related test methods of these devices. Based on the consensus of the expert group, this paper introduces various test methods and their applications in detail, and expounds the sampling of test data. The aim is to unify understanding, promote thestandardization of artificial intelligence medical device performance evaluation methods, and finally boost the high-quality development of artificial intelligence medical devices.

     

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