AI support for accurate and fast radiological diagnosis of COVID-19: an international multicenter, multivendor CT study.

Detalles Bibliográficos
Publicado en:European Radiology Vol. 33; no. 6; pp. 4280 - 4292
Autores principales: Meng, Fanyang, Kottlors, Jonathan, Shahzad, Rahil, Liu, Haifeng, Fervers, Philipp, Jin, Yinhua, Rinneburger, Miriam, Le, Dou, Weisthoff, Mathilda, Liu, Wenyun, Ni, Mengzhe, Sun, Ye, An, Liying, Huai, Xiaochen, Móré, Dorottya, Giannakis, Athanasios, Kaltenborn, Isabel, Bucher, Andreas, Maintz, David, Zhang, Lei
Formato: Journal Article
Publicado: Springer Nature Jun2023
Acceso en línea:Ver este registro en EBSCOhost
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        atl: AI support for accurate and fast radiological diagnosis of COVID-19: an international multicenter, multivendor CT study.
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          Meng, Fanyang
          Kottlors, Jonathan
          Shahzad, Rahil
          Liu, Haifeng
          Fervers, Philipp
          Jin, Yinhua
          Rinneburger, Miriam
          Le, Dou
          Weisthoff, Mathilda
          Liu, Wenyun
          Ni, Mengzhe
          Sun, Ye
          An, Liying
          Huai, Xiaochen
          Móré, Dorottya
          Giannakis, Athanasios
          Kaltenborn, Isabel
          Bucher, Andreas
          Maintz, David
          Zhang, Lei
        affil: Department of Radiology, The First Hospital of Ji Lin University, No. 1 Xinmin Street, 130012, Changchun, China
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      pubtype: Academic Journal
      doctype: Journal Article
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    language: English
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