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Relation of Quantitative Histologic and Radiologic Breast Tissue Composition Metrics With Invasive Breast Cancer Risk.
Abubakar, Mustapha; Fan, Shaoqi; Bowles, Erin Aiello; Widemann, Lea; Duggan, Máire A; Pfeiffer, Ruth M; Falk, Roni T; Lawrence, Scott; Richert-Boe, Kathryn; Glass, Andrew G; Kimes, Teresa M; Figueroa, Jonine D; Rohan, Thomas E; Gierach, Gretchen L.
Afiliação
  • Abubakar M; Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institute of Health, USA.
  • Fan S; Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institute of Health, USA.
  • Bowles EA; Kaiser Permanente Washington Health Research Institute, Seattle, WA, USA.
  • Widemann L; Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institute of Health, USA.
  • Duggan MA; Department of Pathology and Laboratory Medicine, University of Calgary, Calgary, Alberta, Canada.
  • Pfeiffer RM; Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institute of Health, USA.
  • Falk RT; Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institute of Health, USA.
  • Lawrence S; Molecular and Digital Pathology Laboratory, Cancer Genomics Research Laboratory, Leidos Biomedical Research, Inc, Frederick, MD, USA.
  • Richert-Boe K; Kaiser Permanente Center for Health Research, Portland, OR, USA.
  • Glass AG; Kaiser Permanente Center for Health Research, Portland, OR, USA.
  • Kimes TM; Kaiser Permanente Center for Health Research, Portland, OR, USA.
  • Figueroa JD; Usher Institute of Population Health Sciences and Informatics, The University of Edinburgh, Scotland, UK.
  • Rohan TE; Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, NY, USA.
  • Gierach GL; Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institute of Health, USA.
JNCI Cancer Spectr ; 5(3)2021 06.
Article em En | MEDLINE | ID: mdl-33981950
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Mama / Doenças Mamárias / Neoplasias da Mama / Diagnóstico por Computador / Aprendizado de Máquina Supervisionado Tipo de estudo: Diagnostic_studies / Etiology_studies / Observational_studies / Prognostic_studies / Risk_factors_studies Limite: Adult / Aged / Aged80 / Female / Humans / Middle aged Idioma: En Revista: JNCI Cancer Spectr Ano de publicação: 2021 Tipo de documento: Article País de afiliação: Estados Unidos
Texto completo
Imprimir
XML
PubMed Links
Buscar no Google

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Mama / Doenças Mamárias / Neoplasias da Mama / Diagnóstico por Computador / Aprendizado de Máquina Supervisionado Tipo de estudo: Diagnostic_studies / Etiology_studies / Observational_studies / Prognostic_studies / Risk_factors_studies Limite: Adult / Aged / Aged80 / Female / Humans / Middle aged Idioma: En Revista: JNCI Cancer Spectr Ano de publicação: 2021 Tipo de documento: Article País de afiliação: Estados Unidos