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Artificial intelligence system for identification of false-negative interpretations in chest radiographs.
Hwang, Eui Jin; Park, Jongsoo; Hong, Wonju; Lee, Hyun-Ju; Choi, Hyewon; Kim, Hyungjin; Nam, Ju Gang; Goo, Jin Mo; Yoon, Soon Ho; Lee, Chang Hyun; Park, Chang Min.
Afiliación
  • Hwang EJ; Department of Radiology, Seoul National University Hospital, 101 Daehak-ro, Jongno-gu, Seoul, 03080, Korea.
  • Park J; Department of Radiology, Seoul National University College of Medicine, 103 Daehak-ro, Jongno-gu, Seoul, 03080, Korea.
  • Hong W; Department of Radiology, Seoul National University Hospital, 101 Daehak-ro, Jongno-gu, Seoul, 03080, Korea.
  • Lee HJ; Department of Radiology, Seoul National University Hospital, 101 Daehak-ro, Jongno-gu, Seoul, 03080, Korea.
  • Choi H; Department of Radiology, Seoul National University Hospital, 101 Daehak-ro, Jongno-gu, Seoul, 03080, Korea.
  • Kim H; Department of Radiology, Seoul National University College of Medicine, 103 Daehak-ro, Jongno-gu, Seoul, 03080, Korea.
  • Nam JG; Department of Radiology, Seoul National University Hospital, 101 Daehak-ro, Jongno-gu, Seoul, 03080, Korea.
  • Goo JM; Department of Radiology, Chung-Ang University Hospital, 102 Heukseok-ro, Dongjak-gu, Seoul, 06973, Korea.
  • Yoon SH; Department of Radiology, Seoul National University Hospital, 101 Daehak-ro, Jongno-gu, Seoul, 03080, Korea.
  • Lee CH; Department of Radiology, Seoul National University College of Medicine, 103 Daehak-ro, Jongno-gu, Seoul, 03080, Korea.
  • Park CM; Department of Radiology, Seoul National University Hospital, 101 Daehak-ro, Jongno-gu, Seoul, 03080, Korea.
Eur Radiol ; 32(7): 4468-4478, 2022 Jul.
Article en En | MEDLINE | ID: mdl-35195744
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Inteligencia Artificial / Radiólogos Tipo de estudio: Diagnostic_studies / Observational_studies Límite: Humans / Middle aged Idioma: En Revista: Eur Radiol Asunto de la revista: RADIOLOGIA Año: 2022 Tipo del documento: Article Pais de publicación: Alemania
Texto completo
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Inteligencia Artificial / Radiólogos Tipo de estudio: Diagnostic_studies / Observational_studies Límite: Humans / Middle aged Idioma: En Revista: Eur Radiol Asunto de la revista: RADIOLOGIA Año: 2022 Tipo del documento: Article Pais de publicación: Alemania