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医学人工智能产品的数据储备创建及压力测试策略

Strategies for creation of data reserve and stress testing of medical AI products.

作者信息

Chen Huai, Tie Yanmei, Cao Xinhua, Young Geoffrey S, Xu Xiaoyin

机构信息

Department of Radiology, The Second Affiliated Hospital of Guangzhou Medical University, Guangzhou, Guangdong, China.

Department of Neurosurgery, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.

出版信息

BMJ Health Care Inform. 2024 Dec 4;31(1):e101184. doi: 10.1136/bmjhci-2024-101184.

Abstract

With the fast development of artificial intelligence (AI) and its applications in medicine, it is often said that the time for intelligent medicine is arriving, if not already have arrived. While there is no doubt that AI-centred intelligent medicine will transform current healthcare, it is necessary to test and re-test medical AI (MAI) products before they are implemented in the real world. From the perspective of ensuring safety, accuracy and efficiency, it is imperative that MAIs undergo stress tests in a systematic and comprehensive manner where stress tests subject MAIs to workloads and environments beyond tests carried out by their developers. In such stress tests, potential bottlenecks or failures of MAIs may be identified and fed back to developers to optimise the products. To avoid bias and ensure fairness, stress tests should be prepared and administered by an independent body.

摘要

随着人工智能(AI)的快速发展及其在医学领域的应用,人们常说智能医学的时代即将到来,即便尚未真正到来。毫无疑问,以AI为核心的智能医学将改变当前的医疗保健状况,但在将医疗AI(MAI)产品应用于现实世界之前,有必要对其进行反复测试。从确保安全性、准确性和效率的角度来看,MAI必须以系统且全面的方式进行压力测试,在这种测试中,MAI要承受超出其开发者所进行测试的工作量和环境。在这样的压力测试中,可能会识别出MAI的潜在瓶颈或故障,并反馈给开发者以优化产品。为避免偏差并确保公平性,压力测试应由独立机构准备和实施。

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