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Bilateral adaptive graph convolutional network on CT based Covid-19 diagnosis with uncertainty-aware consensus-assisted multiple instance learning.
Meng, Yanda; Bridge, Joshua; Addison, Cliff; Wang, Manhui; Merritt, Cristin; Franks, Stu; Mackey, Maria; Messenger, Steve; Sun, Renrong; Fitzmaurice, Thomas; McCann, Caroline; Li, Qiang; Zhao, Yitian; Zheng, Yalin.
Afiliación
  • Meng Y; Department of Eye and Vision Science, University of Liverpool, Liverpool, United Kingdom.
  • Bridge J; Department of Eye and Vision Science, University of Liverpool, Liverpool, United Kingdom.
  • Addison C; Advanced Research Computing, University of Liverpool, Liverpool, United Kingdom.
  • Wang M; Advanced Research Computing, University of Liverpool, Liverpool, United Kingdom.
  • Merritt C; Alces Flight Limited, Bicester, United Kingdom.
  • Franks S; Alces Flight Limited, Bicester, United Kingdom.
  • Mackey M; Amazon Web Services, 60 Holborn Viaduct, London, United Kingdom.
  • Messenger S; Amazon Web Services, 60 Holborn Viaduct, London, United Kingdom.
  • Sun R; Department of Radiology, Hubei Provincial Hospital of Integrated Chinese and Western Medicine, Hubei University of Chinese Medicine, Wuhan, China.
  • Fitzmaurice T; Adult Cystic Fibrosis Unit, Liverpool Heart and Chest Hospital NHS Foundation Trust, Liverpool, United Kingdom.
  • McCann C; Radiology, Liverpool Heart and Chest Hospital NHS Foundation Trust, United Kingdom.
  • Li Q; The Affiliated People's Hospital of Ningbo University, Ningbo, China.
  • Zhao Y; The Affiliated People's Hospital of Ningbo University, Ningbo, China; Cixi Institute of Biomedical Engineering, Ningbo Institute of Materials Technology and Engineering, Chinese Academy of Science, Ningbo, China. Electronic address: yitian.zhao@nimte.ac.cn.
  • Zheng Y; Department of Eye and Vision Science, University of Liverpool, Liverpool, United Kingdom; Liverpool Centre for Cardiovascular Science, University of Liverpool and Liverpool Heart & Chest Hospital, Liverpool, United Kingdom. Electronic address: yalin.zheng@liverpool.ac.uk.
Med Image Anal ; 84: 102722, 2023 02.
Article en En | MEDLINE | ID: mdl-36574737
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Texto completo: 1 Base de datos: MEDLINE Asunto principal: Prueba de COVID-19 / COVID-19 Tipo de estudio: Diagnostic_studies / Guideline / Prognostic_studies Límite: Humans Idioma: En Revista: Med Image Anal Asunto de la revista: DIAGNOSTICO POR IMAGEM Año: 2023 Tipo del documento: Article País de afiliación: Reino Unido
Texto completo
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Texto completo: 1 Base de datos: MEDLINE Asunto principal: Prueba de COVID-19 / COVID-19 Tipo de estudio: Diagnostic_studies / Guideline / Prognostic_studies Límite: Humans Idioma: En Revista: Med Image Anal Asunto de la revista: DIAGNOSTICO POR IMAGEM Año: 2023 Tipo del documento: Article País de afiliación: Reino Unido