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Artificial intelligence in radiation oncology.
Huynh, Elizabeth; Hosny, Ahmed; Guthier, Christian; Bitterman, Danielle S; Petit, Steven F; Haas-Kogan, Daphne A; Kann, Benjamin; Aerts, Hugo J W L; Mak, Raymond H.
Afiliación
  • Huynh E; Artificial Intelligence in Medicine (AIM) Program, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.
  • Hosny A; Department of Radiation Oncology, Dana-Farber Cancer Institute, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.
  • Guthier C; Artificial Intelligence in Medicine (AIM) Program, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.
  • Bitterman DS; Department of Radiation Oncology, Dana-Farber Cancer Institute, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.
  • Petit SF; Department of Radiation Oncology, Dana-Farber Cancer Institute, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.
  • Haas-Kogan DA; Artificial Intelligence in Medicine (AIM) Program, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.
  • Kann B; Department of Radiation Oncology, Dana-Farber Cancer Institute, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.
  • Aerts HJWL; Computational Health Informatics Program, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA.
  • Mak RH; Department of Radiation Oncology, Erasmus MC Cancer Institute, Rotterdam, The Netherlands.
Nat Rev Clin Oncol ; 17(12): 771-781, 2020 12.
Article en En | MEDLINE | ID: mdl-32843739
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Inteligencia Artificial / Oncología por Radiación / Neoplasias Tipo de estudio: Qualitative_research Límite: Humans Idioma: En Revista: Nat Rev Clin Oncol Asunto de la revista: NEOPLASIAS Año: 2020 Tipo del documento: Article País de afiliación: Estados Unidos Pais de publicación: Reino Unido
Texto completo
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Inteligencia Artificial / Oncología por Radiación / Neoplasias Tipo de estudio: Qualitative_research Límite: Humans Idioma: En Revista: Nat Rev Clin Oncol Asunto de la revista: NEOPLASIAS Año: 2020 Tipo del documento: Article País de afiliación: Estados Unidos Pais de publicación: Reino Unido