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影像人工智能:放射科医生解决健康公平问题的框架,选自多元化、公平性与包容性特刊。

Imaging Artificial Intelligence: A Framework for Radiologists to Address Health Equity, From the Special Series on DEI.

机构信息

Department of Diagnostic Radiology, Yale University School of Medicine, 789 Howard Ave, PO Box 20842, New Haven, CT 06520.

Jefferson Health, Philadelphia, PA.

出版信息

AJR Am J Roentgenol. 2023 Sep;221(3):302-308. doi: 10.2214/AJR.22.28802. Epub 2023 Feb 22.

Abstract

Artificial intelligence (AI) holds promise for helping patients access new and individualized health care pathways while increasing efficiencies for health care practitioners. Radiology has been at the forefront of this technology in medicine; many radiology practices are implementing and trialing AI-focused products. AI also holds great promise for reducing health disparities and promoting health equity. Radiology is ideally positioned to help reduce disparities given its central and critical role in patient care. The purposes of this article are to discuss the potential benefits and pitfalls of deploying AI algorithms in radiology, specifically highlighting the impact of AI on health equity; to explore ways to mitigate drivers of inequity; and to enhance pathways for creating better health care for all individuals, centering on a practical framework that helps radiologists address health equity during deployment of new tools.

摘要

人工智能(AI)有望帮助患者获得新的个性化医疗途径,同时提高医疗从业者的效率。放射科一直处于该技术在医学领域的前沿;许多放射科实践正在实施和试验以 AI 为重点的产品。人工智能在减少健康差距和促进健康公平方面也具有巨大的潜力。鉴于放射科在患者护理中的核心和关键作用,它是帮助减少差异的理想选择。本文的目的是讨论在放射科部署 AI 算法的潜在益处和陷阱,特别是强调 AI 对健康公平的影响;探讨减轻不公平驱动因素的方法;并增强为所有人创造更好医疗保健的途径,以帮助放射科医生在部署新工具时解决公平问题的实用框架为中心。

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