Towards Fairness in Artificial Intelligence for Medical Imaging: Identification and Mitigation of Biases in the Roadmap From Data Commons to Model Design and Deployment

被引：0
|
作者：
Drukker, K. [1 ]
Chen, W. [2 ]
Gichoya, J. [3 ]
Gruszauskas, N. [1 ]
Kalpathy-Cramer, J. [4 ]
Koyejo, S. [5 ]
Myers, K. [1 ,2 ]
Sa, R. [6 ]
Sahiner, B. [2 ]
Whitney, H. [7 ]
Zhang, Z. [8 ]
Giger, M. [1 ]
机构：
[1] Univ Chicago, Chicago, IL 60637 USA
[2] US FDA, Silver Spring, MD USA
[3] Emory Univ, Atlanta, GA 30322 USA
[4] MGH Harvard, Boston, MA USA
[5] Univ Illinois, Champaign, IL USA
[6] Univ Calif San Diego, NIH, La Jolla, CA 92093 USA
[7] Wheaton Coll, Wheaton, IL 60187 USA
[8] Jefferson Hlth, Philadelphia, PA USA
来源：
MEDICAL PHYSICS | 2022年 / 49卷 / 06期
基金：
美国国家卫生研究院;
关键词：
D O I：
暂无
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：
SU-H430-Ie
引用
收藏
页码：E232 / E232
页数：1
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  • [2] Ophthalmic Imaging Roadmap for Artificial Intelligence: from Data to Deployment
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  • [3] Preventing Artificial Intelligence in Medical Imaging From Perpetuating Health Care Biases and Disparities
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    Flanders, Adam E.
    Lungren, Matthew P.
    Mendelson, David S.
    Rudie, Jeffrey D.
    Wang, Ge
    Kandarpa, Krishna
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