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将人工智能算法临床应用及实施于内镜检查实践的框架与指标:美国胃肠内镜学会人工智能特别工作组的建议

Framework and metrics for the clinical use and implementation of artificial intelligence algorithms into endoscopy practice: recommendations from the American Society for Gastrointestinal Endoscopy Artificial Intelligence Task Force.

作者信息

Parasa Sravanthi, Repici Alessandro, Berzin Tyler, Leggett Cadman, Gross Seth A, Sharma Prateek

机构信息

Department of Gastroenterology, Swedish Medical Center, Seattle, Washington, USA.

Digestive Endoscopy Department, Humanitas Research Hospital & University, Milano, Italy.

出版信息

Gastrointest Endosc. 2023 May;97(5):815-824.e1. doi: 10.1016/j.gie.2022.10.016. Epub 2023 Feb 8.

Abstract

In the past few years, we have seen a surge in the development of relevant artificial intelligence (AI) algorithms addressing a variety of needs in GI endoscopy. To accept AI algorithms into clinical practice, their effectiveness, clinical value, and reliability need to be rigorously assessed. In this article, we provide a guiding framework for all stakeholders in the endoscopy AI ecosystem regarding the standards, metrics, and evaluation methods for emerging and existing AI applications to aid in their clinical adoption and implementation. We also provide guidance and best practices for evaluation of AI technologies as they mature in the endoscopy space. Note, this is a living document; periodic updates will be published as progress is made and applications evolve in the field of AI in endoscopy.

摘要

在过去几年中,我们看到针对胃肠内镜检查中各种需求的相关人工智能(AI)算法蓬勃发展。要将AI算法应用于临床实践,需要对其有效性、临床价值和可靠性进行严格评估。在本文中,我们为内镜AI生态系统中的所有利益相关者提供了一个指导框架,涉及新兴和现有AI应用的标准、指标及评估方法,以帮助它们在临床中得到采用和实施。我们还为内镜领域中成熟的AI技术评估提供指导和最佳实践。请注意,这是一份动态文件;随着内镜AI领域取得进展和应用不断发展,将定期发布更新内容。

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