Your browser doesn't support javascript.
loading
Development and Validation of an Automated Image-Based Deep Learning Platform for Sarcopenia Assessment in Head and Neck Cancer.
Ye, Zezhong; Saraf, Anurag; Ravipati, Yashwanth; Hoebers, Frank; Catalano, Paul J; Zha, Yining; Zapaishchykova, Anna; Likitlersuang, Jirapat; Guthier, Christian; Tishler, Roy B; Schoenfeld, Jonathan D; Margalit, Danielle N; Haddad, Robert I; Mak, Raymond H; Naser, Mohamed; Wahid, Kareem A; Sahlsten, Jaakko; Jaskari, Joel; Kaski, Kimmo; Mäkitie, Antti A; Fuller, Clifton D; Aerts, Hugo J W L; Kann, Benjamin H.
Affiliation
  • Ye Z; Artificial Intelligence in Medicine Program, Mass General Brigham, Harvard Medical School, Boston, Massachusetts.
  • Saraf A; Department of Radiation Oncology, Dana-Farber Cancer Institute and Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts.
  • Ravipati Y; Artificial Intelligence in Medicine Program, Mass General Brigham, Harvard Medical School, Boston, Massachusetts.
  • Hoebers F; Department of Radiation Oncology, Dana-Farber Cancer Institute and Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts.
  • Catalano PJ; Artificial Intelligence in Medicine Program, Mass General Brigham, Harvard Medical School, Boston, Massachusetts.
  • Zha Y; Department of Radiation Oncology, Dana-Farber Cancer Institute and Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts.
  • Zapaishchykova A; Artificial Intelligence in Medicine Program, Mass General Brigham, Harvard Medical School, Boston, Massachusetts.
  • Likitlersuang J; Department of Radiation Oncology, Dana-Farber Cancer Institute and Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts.
  • Guthier C; Department of Radiation Oncology (Maastro), GROW School for Oncology and Reproduction, Maastricht University Medical Center+, Maastricht, the Netherlands.
  • Tishler RB; Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, Massachusetts.
  • Schoenfeld JD; Department of Data Science, Dana-Farber Cancer Institute, Harvard Medical School, Boston, Massachusetts.
  • Margalit DN; Artificial Intelligence in Medicine Program, Mass General Brigham, Harvard Medical School, Boston, Massachusetts.
  • Haddad RI; Department of Radiation Oncology, Dana-Farber Cancer Institute and Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts.
  • Mak RH; Artificial Intelligence in Medicine Program, Mass General Brigham, Harvard Medical School, Boston, Massachusetts.
  • Naser M; Department of Radiation Oncology, Dana-Farber Cancer Institute and Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts.
  • Wahid KA; Radiology and Nuclear Medicine, CARIM and GROW, Maastricht University, Maastricht, the Netherlands.
  • Sahlsten J; Artificial Intelligence in Medicine Program, Mass General Brigham, Harvard Medical School, Boston, Massachusetts.
  • Jaskari J; Department of Radiation Oncology, Dana-Farber Cancer Institute and Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts.
  • Kaski K; Artificial Intelligence in Medicine Program, Mass General Brigham, Harvard Medical School, Boston, Massachusetts.
  • Mäkitie AA; Department of Radiation Oncology, Dana-Farber Cancer Institute and Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts.
  • Fuller CD; Department of Radiation Oncology, Dana-Farber Cancer Institute and Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts.
  • Aerts HJWL; Department of Radiation Oncology, Dana-Farber Cancer Institute and Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts.
  • Kann BH; Department of Radiation Oncology, Dana-Farber Cancer Institute and Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts.
JAMA Netw Open ; 6(8): e2328280, 2023 08 01.
Article in En | MEDLINE | ID: mdl-37561460
Subject(s)
Fulltext
Print
XML
PubMed Links
Search on Google

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Sarcopenia / Deep Learning / Head and Neck Neoplasms Type of study: Guideline / Observational_studies / Prognostic_studies / Risk_factors_studies Limits: Female / Humans / Male / Middle aged Language: En Journal: JAMA Netw Open Year: 2023 Type: Article
Fulltext
Print
XML
PubMed Links
Search on Google

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Sarcopenia / Deep Learning / Head and Neck Neoplasms Type of study: Guideline / Observational_studies / Prognostic_studies / Risk_factors_studies Limits: Female / Humans / Male / Middle aged Language: En Journal: JAMA Netw Open Year: 2023 Type: Article