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Deep convolutional neural networks to predict cardiovascular risk from computed tomography.
Zeleznik, Roman; Foldyna, Borek; Eslami, Parastou; Weiss, Jakob; Alexander, Ivanov; Taron, Jana; Parmar, Chintan; Alvi, Raza M; Banerji, Dahlia; Uno, Mio; Kikuchi, Yasuka; Karady, Julia; Zhang, Lili; Scholtz, Jan-Erik; Mayrhofer, Thomas; Lyass, Asya; Mahoney, Taylor F; Massaro, Joseph M; Vasan, Ramachandran S; Douglas, Pamela S; Hoffmann, Udo; Lu, Michael T; Aerts, Hugo J W L.
Afiliação
  • Zeleznik R; Artificial Intelligence in Medicine (AIM) Program, Mass General Brigham, Harvard Medical School, Boston, MA, USA.
  • Foldyna B; Cardiovascular Imaging Research Center, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA.
  • Eslami P; Department of Radiation Oncology, Brigham and Women's Hospital, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA, USA.
  • Weiss J; Artificial Intelligence in Medicine (AIM) Program, Mass General Brigham, Harvard Medical School, Boston, MA, USA.
  • Alexander I; Cardiovascular Imaging Research Center, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA.
  • Taron J; Cardiovascular Imaging Research Center, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA.
  • Parmar C; Artificial Intelligence in Medicine (AIM) Program, Mass General Brigham, Harvard Medical School, Boston, MA, USA.
  • Alvi RM; Cardiovascular Imaging Research Center, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA.
  • Banerji D; Department of Radiation Oncology, Brigham and Women's Hospital, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA, USA.
  • Uno M; Department of Diagnostic and Interventional Radiology, Eberhard Karls University of Tübingen, Tübingen, Germany.
  • Kikuchi Y; Cardiovascular Imaging Research Center, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA.
  • Karady J; Cardiovascular Imaging Research Center, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA.
  • Zhang L; Department of Diagnostic and Interventional Radiology, Eberhard Karls University of Tübingen, Tübingen, Germany.
  • Scholtz JE; Artificial Intelligence in Medicine (AIM) Program, Mass General Brigham, Harvard Medical School, Boston, MA, USA.
  • Mayrhofer T; Department of Radiation Oncology, Brigham and Women's Hospital, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA, USA.
  • Lyass A; Cardiovascular Imaging Research Center, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA.
  • Mahoney TF; Cardiovascular Imaging Research Center, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA.
  • Massaro JM; Cardiovascular Imaging Research Center, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA.
  • Vasan RS; Cardiovascular Imaging Research Center, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA.
  • Douglas PS; Center for Cause of Death Investigation, Faculty of Medicine, Hokkaido University, Sapporo, Hokkaido, Japan.
  • Hoffmann U; Cardiovascular Imaging Research Center, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA.
  • Lu MT; Cardiovascular Imaging Research Group, Heart and Vascular Center, Semmelweis University, Budapest, Hungary.
  • Aerts HJWL; Cardiovascular Imaging Research Center, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA.
Nat Commun ; 12(1): 715, 2021 01 29.
Article em En | MEDLINE | ID: mdl-33514711
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Dor no Peito / Processamento de Imagem Assistida por Computador / Doenças Cardiovasculares / Vasos Coronários / Aprendizado Profundo Tipo de estudo: Diagnostic_studies / Etiology_studies / Guideline / Observational_studies / Prognostic_studies / Risk_factors_studies Limite: Aged / Female / Humans / Male / Middle aged Idioma: En Revista: Nat Commun Assunto da revista: BIOLOGIA / CIENCIA Ano de publicação: 2021 Tipo de documento: Article País de afiliação: Estados Unidos
Texto completo
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PubMed Links
Buscar no Google

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Dor no Peito / Processamento de Imagem Assistida por Computador / Doenças Cardiovasculares / Vasos Coronários / Aprendizado Profundo Tipo de estudo: Diagnostic_studies / Etiology_studies / Guideline / Observational_studies / Prognostic_studies / Risk_factors_studies Limite: Aged / Female / Humans / Male / Middle aged Idioma: En Revista: Nat Commun Assunto da revista: BIOLOGIA / CIENCIA Ano de publicação: 2021 Tipo de documento: Article País de afiliação: Estados Unidos