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  • [\'Department of Medical Imaging, Jinling Hospital, Medical School of Nanjing University, Nanjing, 210002, Jiangsu, China.\', \'Department of Medical Imaging, Taihe Hospital, Shiyan, 442008, Hubei, China.\', \'Department of Medical Imaging, Wuhan First Hospital, Wuhan, 430022, Hubei, China.\', \'Deepwise AI Lab, Beijing, 100080, China.\', \'School of Electronics Engineering and Computer Science, Peking University, Beijing, 10080, China.\', \'Department of Computer Science, The University of Hong Kong, Pok Fu Lam, Hong Kong.\', \'Department of Medical Imaging, Jinling Hospital, Medical School of Nanjing University, Nanjing, 210002, Jiangsu, China. kevinzhlj@163.com.\', \'Department of Medical Imaging, Medical Imaging Center, Nanjing Clinical School, Southern Medical University, 305 Zhongshan East Road, Xuanwu District, Nanjing, 210002, Jiangsu, China. kevinzhlj@163.com.\']
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  • -1
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?:doi
?:doi
  • 10.1007/s00330-020-07044-9
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?:journal
  • European radiology
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  • 32617690
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?:title
  • A deep learning approach to characterize 2019 coronavirus disease (COVID-19) pneumonia in chest CT images.
?:type
?:year
  • 2020

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