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关于数字病理学人工智能产品的公开证据。

Public evidence on AI products for digital pathology.

作者信息

Matthews Gillian A, McGenity Clare, Bansal Daljeet, Treanor Darren

机构信息

Leeds Teaching Hospitals NHS Trust, Leeds, UK.

University of Leeds, Leeds, UK.

出版信息

NPJ Digit Med. 2024 Oct 25;7(1):300. doi: 10.1038/s41746-024-01294-3.

Abstract

Novel products applying artificial intelligence (AI)-based methods to digital pathology images are touted to have many uses and benefits. However, publicly available information for products can be variable, with few sources of independent evidence. This review aimed to identify public evidence for AI-based products for digital pathology. Key features of products on the European Economic Area/Great Britain (EEA/GB) markets were examined, including their regulatory approval, intended use, and published validation studies. There were 26 AI-based products that met the inclusion criteria and, of these, 24 had received regulatory approval via the self-certification route as General in vitro diagnostic (IVD) medical devices. Only 10 of the products (38%) had peer-reviewed internal validation studies and 11 products (42%) had peer-reviewed external validation studies. To support transparency an online register was developed using identified public evidence ( https://osf.io/gb84r/ ), which we anticipate will provide an accessible resource on novel devices and support decision making.

摘要

应用基于人工智能(AI)方法处理数字病理图像的新型产品被吹捧为有诸多用途和益处。然而,产品的公开可用信息可能参差不齐,独立证据来源很少。本综述旨在识别基于AI的数字病理产品的公开证据。对欧洲经济区/英国(EEA/GB)市场上产品的关键特征进行了审查,包括其监管批准、预期用途和已发表的验证研究。有26种基于AI的产品符合纳入标准,其中24种已通过自我认证途径获得监管批准,作为通用体外诊断(IVD)医疗器械。只有10种产品(38%)有经过同行评审的内部验证研究,11种产品(42%)有经过同行评审的外部验证研究。为了支持透明度,利用已识别的公开证据开发了一个在线登记册(https://osf.io/gb84r/),我们预计该登记册将提供关于新型设备的可获取资源并支持决策制定。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2b03/11511888/00928f0e7a97/41746_2024_1294_Fig1_HTML.jpg

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