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Decoding biological age from face photographs using deep learning.
Zalay, Osbert; Bontempi, Dennis; Bitterman, Danielle S; Birkbak, Nicolai; Shyr, Derek; Haugg, Fridolin; Qian, Jack M; Roberts, Hannah; Perni, Subha; Prudente, Vasco; Pai, Suraj; Dekker, Andre; Haibe-Kains, Benjamin; Guthier, Christian; Balboni, Tracy; Warren, Laura; Krishan, Monica; Kann, Benjamin H; Swanton, Charles; Ruysscher, Dirk De; Mak, Raymond H; Aerts, Hugo Jwl.
Afiliação
  • Zalay O; Artificial Intelligence in Medicine (AIM) Program, Mass General Brigham, Harvard Medical School, Boston, United States of America.
  • Bontempi D; Department of Radiation Oncology, Brigham and Women's Hospital, Dana-Farber Cancer Institute, Harvard Medical School, Boston, United States of America.
  • Bitterman DS; Division of Radiation Oncology, Queen's University, Kingston, Canada.
  • Birkbak N; Artificial Intelligence in Medicine (AIM) Program, Mass General Brigham, Harvard Medical School, Boston, United States of America.
  • Shyr D; Department of Radiation Oncology, Brigham and Women's Hospital, Dana-Farber Cancer Institute, Harvard Medical School, Boston, United States of America.
  • Haugg F; Radiology and Nuclear Medicine, CARIM & GROW, Maastricht University, Maastricht, The Netherlands.
  • Qian JM; Department of Radiation Oncology (MAASTRO), Maastricht University, Maastricht, The Netherlands.
  • Roberts H; Artificial Intelligence in Medicine (AIM) Program, Mass General Brigham, Harvard Medical School, Boston, United States of America.
  • Perni S; Department of Radiation Oncology, Brigham and Women's Hospital, Dana-Farber Cancer Institute, Harvard Medical School, Boston, United States of America.
  • Prudente V; Department of Molecular Medicine, Aarhus University Hospital, Aarhus, Denmark.
  • Pai S; Department of Clinical Medicine, Aarhus University, Aarhus, Denmark.
  • Dekker A; Bioinformatics Research Center, Aarhus University, Aarhus, Denmark.
  • Haibe-Kains B; Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston.
  • Guthier C; Artificial Intelligence in Medicine (AIM) Program, Mass General Brigham, Harvard Medical School, Boston, United States of America.
  • Balboni T; Department of Radiation Oncology, Brigham and Women's Hospital, Dana-Farber Cancer Institute, Harvard Medical School, Boston, United States of America.
  • Warren L; Artificial Intelligence in Medicine (AIM) Program, Mass General Brigham, Harvard Medical School, Boston, United States of America.
  • Krishan M; Department of Radiation Oncology, Brigham and Women's Hospital, Dana-Farber Cancer Institute, Harvard Medical School, Boston, United States of America.
  • Kann BH; Artificial Intelligence in Medicine (AIM) Program, Mass General Brigham, Harvard Medical School, Boston, United States of America.
  • Swanton C; Department of Radiation Oncology, Brigham and Women's Hospital, Dana-Farber Cancer Institute, Harvard Medical School, Boston, United States of America.
  • Ruysscher D; Artificial Intelligence in Medicine (AIM) Program, Mass General Brigham, Harvard Medical School, Boston, United States of America.
  • Mak RH; Department of Radiation Oncology, Brigham and Women's Hospital, Dana-Farber Cancer Institute, Harvard Medical School, Boston, United States of America.
  • Aerts HJ; Artificial Intelligence in Medicine (AIM) Program, Mass General Brigham, Harvard Medical School, Boston, United States of America.
medRxiv ; 2023 Sep 12.
Article em En | MEDLINE | ID: mdl-37745558
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies Idioma: En Ano de publicação: 2023 Tipo de documento: Article
Texto completo
Imprimir
XML
PubMed Links
Buscar no Google

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies Idioma: En Ano de publicação: 2023 Tipo de documento: Article