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Predicting clinical outcomes from large scale cancer genomic profiles with deep survival models.
Yousefi, Safoora; Amrollahi, Fatemeh; Amgad, Mohamed; Dong, Chengliang; Lewis, Joshua E; Song, Congzheng; Gutman, David A; Halani, Sameer H; Velazquez Vega, Jose Enrique; Brat, Daniel J; Cooper, Lee A D.
Afiliación
  • Yousefi S; Department of Biomedical Informatics, Emory University School of Medicine, Atlanta, GA, 30322, USA.
  • Amrollahi F; Department of Biomedical Informatics, Emory University School of Medicine, Atlanta, GA, 30322, USA.
  • Amgad M; Department of Biomedical Informatics, Emory University School of Medicine, Atlanta, GA, 30322, USA.
  • Dong C; Department of Biostatistics, Mailman School of Public Health, Columbia University, New York, NY, 10032, USA.
  • Lewis JE; Department of Biomedical Engineering, Georgia Institute of Technology/Emory University School of Medicine, Atlanta, GA, 30322, USA.
  • Song C; Department of Computer Science, Cornell University, Ithaca, NY, 14850, USA.
  • Gutman DA; Department of Neurology, Emory University School of Medicine, Atlanta, GA, 30322, USA.
  • Halani SH; Emory University School of Medicine, Atlanta, GA, 30322, USA.
  • Velazquez Vega JE; Department of Pathology and Laboratory Medicine, Emory University School of Medicine, Atlanta, GA, 30322, USA.
  • Brat DJ; Department of Pathology and Laboratory Medicine, Emory University School of Medicine, Atlanta, GA, 30322, USA.
  • Cooper LAD; Winship Cancer Institute, Emory University, Atlanta, GA, 30322, USA.
Sci Rep ; 7(1): 11707, 2017 09 15.
Article en En | MEDLINE | ID: mdl-28916782
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Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Pronóstico / Sobrevida / Programas Informáticos / Genómica / Aprendizaje Profundo Tipo de estudio: Prognostic_studies / Risk_factors_studies Límite: Humans Idioma: En Revista: Sci Rep Año: 2017 Tipo del documento: Article País de afiliación: Estados Unidos
Texto completo
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Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Pronóstico / Sobrevida / Programas Informáticos / Genómica / Aprendizaje Profundo Tipo de estudio: Prognostic_studies / Risk_factors_studies Límite: Humans Idioma: En Revista: Sci Rep Año: 2017 Tipo del documento: Article País de afiliación: Estados Unidos