Evaluation and Regulation of Artificial Intelligence Medical Devices for Clinical Decision Support.

IF 6 Q1 MATHEMATICAL & COMPUTATIONAL BIOLOGY Annual Review of Biomedical Data Science Pub Date : 2025-08-01 Epub Date: 2025-02-19 DOI:10.1146/annurev-biodatasci-103123-095824
Gary E Weissman
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Abstract

Artificial intelligence (AI) methods were first developed nearly seven decades ago. Only in recent years have they demonstrated their potential to improve clinical care at the bedside. AI systems are now capable of interpreting, predicting, and even generating important medical information. AI medical devices share many similarities with traditional medical devices but also diverge from them in important ways. Despite widespread optimism and enthusiasm surrounding the use of such devices to improve care processes, patient outcomes, and the healthcare experience for patients, caregivers, and clinicians alike, little evidence exists so far for their effectiveness in practice. Even less is known about the safety or equity of AI medical devices. As with any new technology, this exciting time is accompanied by appropriate questions regarding if, how much, when, and who such AI systems really help. Different stakeholders, ranging from patients to clinicians to industry device developers, may have divergent preferences or assessments of risk and benefits, warranting an informed public discussion to guide emerging regulatory efforts. This review summarizes the rapidly evolving recent efforts and evidence related to the regulation and evaluation of AI medical devices and highlights opportunities for future work to ensure their effectiveness, safety, and equity.

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临床决策支持人工智能医疗器械的评价与规范
人工智能(AI)方法最早是在近70年前开发出来的。直到最近几年,它们才显示出改善床边临床护理的潜力。人工智能系统现在能够解释、预测,甚至生成重要的医疗信息。人工智能医疗设备与传统医疗设备有许多相似之处,但在重要方面也有所不同。尽管人们普遍对使用此类设备来改善护理流程、患者预后以及患者、护理人员和临床医生的医疗保健体验感到乐观和热情,但迄今为止,几乎没有证据表明它们在实践中的有效性。人们对人工智能医疗设备的安全性或公平性了解得更少。与任何新技术一样,这一激动人心的时刻也伴随着一些适当的问题,如人工智能系统是否、多大程度、何时以及谁真正有帮助。不同的利益相关者,从患者到临床医生再到行业设备开发商,可能有不同的偏好或风险和收益评估,因此需要进行知情的公众讨论,以指导新兴的监管工作。本综述总结了近期与人工智能医疗器械监管和评估相关的快速发展的努力和证据,并强调了未来工作的机会,以确保其有效性、安全性和公平性。
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来源期刊
CiteScore
11.10
自引率
1.70%
发文量
0
期刊介绍: The Annual Review of Biomedical Data Science provides comprehensive expert reviews in biomedical data science, focusing on advanced methods to store, retrieve, analyze, and organize biomedical data and knowledge. The scope of the journal encompasses informatics, computational, artificial intelligence (AI), and statistical approaches to biomedical data, including the sub-fields of bioinformatics, computational biology, biomedical informatics, clinical and clinical research informatics, biostatistics, and imaging informatics. The mission of the journal is to identify both emerging and established areas of biomedical data science, and the leaders in these fields.
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