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Deep-Learning to Predict BRCA Mutation and Survival from Digital H&E Slides of Epithelial Ovarian Cancer.
Nero, Camilla; Boldrini, Luca; Lenkowicz, Jacopo; Giudice, Maria Teresa; Piermattei, Alessia; Inzani, Frediano; Pasciuto, Tina; Minucci, Angelo; Fagotti, Anna; Zannoni, Gianfranco; Valentini, Vincenzo; Scambia, Giovanni.
Afiliação
  • Nero C; Fondazione Policlinico Agostino Gemelli, IRCCS, Gynecology and Obstetrics, 00168 Rome, Italy.
  • Boldrini L; Fondazione Policlinico Agostino Gemelli, IRCCS, Radiomics Core Facility, 00168 Rome, Italy.
  • Lenkowicz J; Fondazione Policlinico Agostino Gemelli, IRCCS, Radiomics Core Facility, 00168 Rome, Italy.
  • Giudice MT; Fondazione Policlinico Agostino Gemelli, IRCCS, Gynecology and Obstetrics, 00168 Rome, Italy.
  • Piermattei A; Fondazione Policlinico Agostino Gemelli, IRCCS, Pathology, 00168 Rome, Italy.
  • Inzani F; Fondazione Policlinico Agostino Gemelli, IRCCS, Pathology, 00168 Rome, Italy.
  • Pasciuto T; Fondazione Policlinico Agostino Gemelli, IRCCS, Data Collection Core Facility, 00168 Rome, Italy.
  • Minucci A; Fondazione Policlinico Agostino Gemelli, IRCCS, Genomics Core Facility, 00168 Rome, Italy.
  • Fagotti A; Fondazione Policlinico Agostino Gemelli, IRCCS, Gynecology and Obstetrics, 00168 Rome, Italy.
  • Zannoni G; Fondazione Policlinico Agostino Gemelli, IRCCS, Pathology, 00168 Rome, Italy.
  • Valentini V; Fondazione Policlinico Agostino Gemelli, IRCCS, Radiation Oncology, 00168 Rome, Italy.
  • Scambia G; Fondazione Policlinico Agostino Gemelli, IRCCS, Gynecology and Obstetrics, 00168 Rome, Italy.
Int J Mol Sci ; 23(19)2022 Sep 26.
Article em En | MEDLINE | ID: mdl-36232628
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Neoplasias Ovarianas / Aprendizado Profundo Tipo de estudo: Diagnostic_studies / Prognostic_studies / Risk_factors_studies Limite: Female / Humans Idioma: En Ano de publicação: 2022 Tipo de documento: Article
Texto completo
Imprimir
XML
PubMed Links
Buscar no Google

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Neoplasias Ovarianas / Aprendizado Profundo Tipo de estudo: Diagnostic_studies / Prognostic_studies / Risk_factors_studies Limite: Female / Humans Idioma: En Ano de publicação: 2022 Tipo de documento: Article