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Deep learning-based diagnostic model for predicting complications after gastrectomy.
Fukuyo, Ryosuke; Tokunaga, Masanori; Umebayashi, Yuya; Saito, Toshifumi; Okuno, Keisuke; Sato, Yuya; Saito, Katsumasa; Fujiwara, Naoto; Kinugasa, Yusuke.
Afiliação
  • Fukuyo R; Department of Gastrointestinal surgery, Tokyo Medical and Dental University, Tokyo, Japan.
  • Tokunaga M; Department of Gastrointestinal surgery, Tokyo Medical and Dental University, Tokyo, Japan.
  • Umebayashi Y; Department of Gastrointestinal surgery, Tokyo Medical and Dental University, Tokyo, Japan.
  • Saito T; Department of Gastrointestinal surgery, Tokyo Medical and Dental University, Tokyo, Japan.
  • Okuno K; Department of Gastrointestinal surgery, Tokyo Medical and Dental University, Tokyo, Japan.
  • Sato Y; Department of Gastrointestinal surgery, Tokyo Medical and Dental University, Tokyo, Japan.
  • Saito K; Department of Gastrointestinal surgery, Tokyo Medical and Dental University, Tokyo, Japan.
  • Fujiwara N; Department of Gastrointestinal surgery, Tokyo Medical and Dental University, Tokyo, Japan.
  • Kinugasa Y; Department of Gastrointestinal surgery, Tokyo Medical and Dental University, Tokyo, Japan.
Asian J Endosc Surg ; 16(2): 210-217, 2023 Apr.
Article em En | MEDLINE | ID: mdl-36351358
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Neoplasias Gástricas / Aprendizado Profundo Idioma: En Ano de publicação: 2023 Tipo de documento: Article
Texto completo
Imprimir
XML
PubMed Links
Buscar no Google

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Neoplasias Gástricas / Aprendizado Profundo Idioma: En Ano de publicação: 2023 Tipo de documento: Article