Sequestration of imaging studies in MIDRC: stratified sampling to balance demographic characteristics of patients in a multi-institutional data commons.

Baughan, Natalie; Whitney, Heather M; Drukker, Karen; Sahiner, Berkman; Hu, Tingting; Kim, Grace Hyun; McNitt-Gray, Michael; Myers, Kyle J; Giger, Maryellen L

Baughan, Natalie; Whitney, Heather M; Drukker, Karen; Sahiner, Berkman; Hu, Tingting; Kim, Grace Hyun; McNitt-Gray, Michael; Myers, Kyle J; Giger, Maryellen L.

Afiliación

Baughan N; University of Chicago, Department of Radiology, Chicago, Illinois, United States.
Whitney HM; University of Chicago, Department of Radiology, Chicago, Illinois, United States.
Drukker K; University of Chicago, Department of Radiology, Chicago, Illinois, United States.
Sahiner B; US Food and Drug Administration, Bethesda, Maryland, United States.
Hu T; US Food and Drug Administration, Bethesda, Maryland, United States.
Kim GH; University of California, Los Angeles, Los Angeles, California, United States.
McNitt-Gray M; University of California, Los Angeles, Los Angeles, California, United States.
Myers KJ; Puente Solutions, Phoenix, Arizona, United States.
Giger ML; University of Chicago, Department of Radiology, Chicago, Illinois, United States.

J Med Imaging (Bellingham) ; 10(6): 064501, 2023 Nov.

Article en En | MEDLINE | ID: mdl-38074627

Palabras clave

COVID-19; Medical Imaging and Data Resource Center; algorithm performance; image database; machine learning; sequestration; stratified sampling

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Texto completo: 1 Banco de datos: MEDLINE Idioma: En Revista: J Med Imaging (Bellingham) Año: 2023 Tipo del documento: Article País de afiliación: Estados Unidos

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Texto completo: 1 Banco de datos: MEDLINE Idioma: En Revista: J Med Imaging (Bellingham) Año: 2023 Tipo del documento: Article País de afiliación: Estados Unidos