Derivation of prognostic contextual histopathological features from whole-slide images of tumours via graph deep learning.

Lee, Yongju; Park, Jeong Hwan; Oh, Sohee; Shin, Kyoungseob; Sun, Jiyu; Jung, Minsun; Lee, Cheol; Kim, Hyojin; Chung, Jin-Haeng; Moon, Kyung Chul; Kwon, Sunghoon

Lee, Yongju; Park, Jeong Hwan; Oh, Sohee; Shin, Kyoungseob; Sun, Jiyu; Jung, Minsun; Lee, Cheol; Kim, Hyojin; Chung, Jin-Haeng; Moon, Kyung Chul; Kwon, Sunghoon.

Afiliação

Lee Y; Department of Electrical and Computer Engineering, Seoul National University, Seoul, Republic of Korea.
Park JH; Department of Pathology, Seoul National University College of Medicine, Seoul, Republic of Korea.
Oh S; Department of Pathology, SMG-SNU Boramae Medical Center, Seoul, Republic of Korea.
Shin K; Medical Research Collaborating Center, SMG-SNU Boramae Medical Center, Seoul, Republic of Korea.
Sun J; Department of Electrical and Computer Engineering, Seoul National University, Seoul, Republic of Korea.
Jung M; Medical Research Collaborating Center, SMG-SNU Boramae Medical Center, Seoul, Republic of Korea.
Lee C; Department of Pathology, Seoul National University College of Medicine, Seoul, Republic of Korea.
Kim H; Department of Pathology, Severance Hospital, Yonsei University College of Medicine, Seoul, Republic of Korea.
Chung JH; Department of Pathology, Seoul National University College of Medicine, Seoul, Republic of Korea.
Moon KC; Department of Pathology, Seoul National University Hospital, Seoul, Republic of Korea.
Kwon S; Department of Pathology, Seoul National University College of Medicine, Seoul, Republic of Korea.

Nat Biomed Eng ; 2022 Aug 18.

Article em En | MEDLINE | ID: mdl-35982331

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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies Idioma: En Revista: Nat Biomed Eng Ano de publicação: 2022 Tipo de documento: Article

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