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Machine Learning Model to Predict Pseudoprogression Versus Progression in Glioblastoma Using MRI: A Multi-Institutional Study (KROG 18-07).
Jang, Bum-Sup; Park, Andrew J; Jeon, Seung Hyuck; Kim, Il Han; Lim, Do Hoon; Park, Shin-Hyung; Lee, Ju Hye; Chang, Ji Hyun; Cho, Kwan Ho; Kim, Jin Hee; Sunwoo, Leonard; Choi, Seung Hong; Kim, In Ah.
Afiliação
  • Jang BS; Department of Radiation Oncology, Seoul National University Bundang Hospital, Seongnam 13620, Korea.
  • Park AJ; Artificial Intelligence Research and Development Laboratory, SELVAS AI Incorporation, Seoul 08594, Korea.
  • Jeon SH; Graduate School of Medical Science and Engineering, Korea Advanced Institute of Science and Technology, Daejeon 34141, Korea.
  • Kim IH; Department of Radiation Oncology, Seoul National University Hospital, Seoul 03080, Korea.
  • Lim DH; Department of Radiation Oncology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul 06351, Korea.
  • Park SH; Department of Radiation Oncology, School of Medicine, Kyungpook National University, Daegu 41944, Korea.
  • Lee JH; Department of Radiation Oncology, Pusan National University Hospital, Busan 49241, Korea.
  • Chang JH; Department of Radiation Oncology, Seoul National University Hospital, Seoul 03080, Korea.
  • Cho KH; The Proton Therapy Center, Research Institute and Hospital, National Cancer Center, Goyang 10408, Korea.
  • Kim JH; Department of Radiation Oncology, Dongsan Medical Center, Keimyung University School of Medicine, Daegu 42601, Korea.
  • Sunwoo L; Department of Radiology, Seoul National University Bundang Hospital, Seongnam 13620, Korea.
  • Choi SH; Department of Radiology, Seoul National University Hospital, Seoul 03080, Korea.
  • Kim IA; Department of Radiation Oncology, Seoul National University Bundang Hospital, Seongnam 13620, Korea.
Cancers (Basel) ; 12(9)2020 Sep 21.
Article em En | MEDLINE | ID: mdl-32967367
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Texto completo: 1 Bases de dados: MEDLINE Tipo de estudo: Prognostic_studies / Risk_factors_studies Idioma: En Revista: Cancers (Basel) Ano de publicação: 2020 Tipo de documento: Article
Texto completo
Adicionar na Minha BVS
Imprimir
XML
PubMed Links
Buscar no Google

Texto completo: 1 Bases de dados: MEDLINE Tipo de estudo: Prognostic_studies / Risk_factors_studies Idioma: En Revista: Cancers (Basel) Ano de publicação: 2020 Tipo de documento: Article