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

被引:6
作者
Davis, Melissa A. [1 ]
Lim, Nicholas [2 ]
Jordan, John [3 ]
Yee, Judy [4 ]
Gichoya, Judy Wawira [5 ]
Lee, Ryan [2 ]
机构
[1] Yale Univ, Sch Med, Dept Diagnost Radiol, 789 Howard Ave,POB 20842, New Haven, CT 06520 USA
[2] Jefferson Hlth, Philadelphia, PA USA
[3] Stanford Univ, Sch Med, Stanford, CA USA
[4] Albert Einstein Coll Med, Montefiore Med Ctr, New York, NY USA
[5] Emory Univ, Dept Biol, Atlanta, GA 30322 USA
关键词
artificial intelligence; governance; health disparities; health equity; DATA SCIENCE INSTITUTE; DISPARITIES; US; SPINE; RACE; CARE; AUGMENTATION; FRACTURES; PATIENT; PAIN;
D O I
10.2214/AJR.22.28802
中图分类号
R8 [特种医学]; R445 [影像诊断学];
学科分类号
1002 ; 100207 ; 1009 ;
摘要
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.
引用
收藏
页码:302 / 308
页数:7
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