Your browser doesn't support javascript.
loading
A whole slide image-based machine learning approach to predict ductal carcinoma in situ (DCIS) recurrence risk.
Klimov, Sergey; Miligy, Islam M; Gertych, Arkadiusz; Jiang, Yi; Toss, Michael S; Rida, Padmashree; Ellis, Ian O; Green, Andrew; Krishnamurti, Uma; Rakha, Emad A; Aneja, Ritu.
Afiliación
  • Klimov S; Department of Biology, Georgia State University, Atlanta, GA, 30303, USA.
  • Miligy IM; Department of Mathematics and Statistics, Georgia State University, Atlanta, GA, USA.
  • Gertych A; Department of Cellular Pathology, University of Nottingham, Nottingham, UK.
  • Jiang Y; Department of Pathology, Cedars-Sinai Medical Center, Los Angeles, CA, USA.
  • Toss MS; Department of Mathematics and Statistics, Georgia State University, Atlanta, GA, USA.
  • Rida P; Department of Cellular Pathology, University of Nottingham, Nottingham, UK.
  • Ellis IO; Department of Biology, Georgia State University, Atlanta, GA, 30303, USA.
  • Green A; Department of Cellular Pathology, University of Nottingham, Nottingham, UK.
  • Krishnamurti U; Department of Cellular Pathology, University of Nottingham, Nottingham, UK.
  • Rakha EA; Department of Pathology, Emory University, Atlanta, GA, USA.
  • Aneja R; Department of Cellular Pathology, University of Nottingham, Nottingham, UK. Emad.Rakha@Nottingham.Ac.Uk.
Breast Cancer Res ; 21(1): 83, 2019 07 29.
Article en En | MEDLINE | ID: mdl-31358020
Asunto(s)
Palabras clave
Texto completo
Imprimir
XML
PubMed Links
Buscar en Google

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Neoplasias de la Mama / Inmunohistoquímica / Biomarcadores de Tumor / Carcinoma Intraductal no Infiltrante / Aprendizaje Automático Tipo de estudio: Etiology_studies / Prognostic_studies / Risk_factors_studies Límite: Adult / Aged / Aged80 / Female / Humans / Middle aged Idioma: En Revista: Breast Cancer Res Asunto de la revista: NEOPLASIAS Año: 2019 Tipo del documento: Article País de afiliación: Estados Unidos
Texto completo
Imprimir
XML
PubMed Links
Buscar en Google

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Neoplasias de la Mama / Inmunohistoquímica / Biomarcadores de Tumor / Carcinoma Intraductal no Infiltrante / Aprendizaje Automático Tipo de estudio: Etiology_studies / Prognostic_studies / Risk_factors_studies Límite: Adult / Aged / Aged80 / Female / Humans / Middle aged Idioma: En Revista: Breast Cancer Res Asunto de la revista: NEOPLASIAS Año: 2019 Tipo del documento: Article País de afiliación: Estados Unidos