医学
间隙
食品药品监督管理局
临床实习
算法
机器学习
医学物理学
过程(计算)
重症监护医学
人工智能
医疗急救
计算机科学
物理疗法
操作系统
泌尿科
作者
Kuan Zhang,Bardia Khosravi,Sanaz Vahdati,Bradley J. Erickson
出处
期刊:Radiology
[Radiological Society of North America]
日期:2024-01-01
卷期号:310 (1)
被引量:4
标识
DOI:10.1148/radiol.230242
摘要
A Food and Drug Administration (FDA)–cleared artificial intelligence (AI) algorithm misdiagnosed a finding as an intracranial hemorrhage in a patient, who was finally diagnosed with an ischemic stroke. This scenario highlights a notable failure mode of AI tools, emphasizing the importance of human-machine interaction. In this report, the authors summarize the review processes by the FDA for software as a medical device and the unique regulatory designs for radiologic AI/machine learning algorithms to ensure their safety in clinical practice. Then the challenges in maximizing the efficacy of these tools posed by their clinical implementation are discussed. © RSNA, 2024
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