Toward fairness in artificial intelligence for medical image analysis: identification and mitigation of potential biases in the roadmap from data collection to model deployment.

Drukker, Karen; Chen, Weijie; Gichoya, Judy; Gruszauskas, Nicholas; Kalpathy-Cramer, Jayashree; Koyejo, Sanmi; Myers, Kyle; Sá, Rui C; Sahiner, Berkman; Whitney, Heather; Zhang, Zi; Giger, Maryellen

Drukker, Karen; Chen, Weijie; Gichoya, Judy; Gruszauskas, Nicholas; Kalpathy-Cramer, Jayashree; Koyejo, Sanmi; Myers, Kyle; Sá, Rui C; Sahiner, Berkman; Whitney, Heather; Zhang, Zi; Giger, Maryellen.

Afiliação

Drukker K; The University of Chicago, Department of Radiology, Chicago, Illinois, United States.
Chen W; US Food and Drug Administration, Division of Imaging, Diagnostics, and Software Reliability, Office of Science and Engineering Laboratories, Center for Devices and Radiological Health, Silver Spring, Maryland, United States.
Gichoya J; Emory University, Department of Radiology, Atlanta, Georgia, United States.
Gruszauskas N; The University of Chicago, Department of Radiology, Chicago, Illinois, United States.
Kalpathy-Cramer J; University of Colorado Anschutz, Department of Ophthalmology, Aurora, Colorado, United States.
Koyejo S; Stanford University, Department of Computer Science, Stanford, California, United States.
Myers K; Puente Solutions LLC, Phoenix, Arizona, United States.
Sá RC; National Institutes of Health, Bethesda, Maryland, United States.
Sahiner B; University of California, San Diego, La Jolla, California, United States.
Whitney H; US Food and Drug Administration, Division of Imaging, Diagnostics, and Software Reliability, Office of Science and Engineering Laboratories, Center for Devices and Radiological Health, Silver Spring, Maryland, United States.
Zhang Z; The University of Chicago, Department of Radiology, Chicago, Illinois, United States.
Giger M; Jefferson Health, Philadelphia, Pennsylvania, United States.

J Med Imaging (Bellingham) ; 10(6): 061104, 2023 Nov.

Article em En | MEDLINE | ID: mdl-37125409

Palavras-chave

artificial intelligence; bias; fairness; machine learning

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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Diagnostic_studies / Guideline / Prognostic_studies / Risk_factors_studies Idioma: En Revista: J Med Imaging (Bellingham) Ano de publicação: 2023 Tipo de documento: Article País de afiliação: Estados Unidos País de publicação: Estados Unidos

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