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  • [\'School of Computer Science and Engineering, South China University of Technology, Guangzhou, 510600, China.\', \'School of Computer Science and Engineering, South China University of Technology, Guangzhou, 510600, China. cszxm@scut.edu.cn.\', \'Department of Medical Imaging, Collaborative Innovation Center for Cancer Medicine, State Key Laboratory of Oncology in South China, Sun Yat-sen University Cancer Center, Guangzhou, 510006, China.\', \'Wuhan Huangpi District Hospital of Traditional Chinese Medicine, 430300, Wuhan, China.\', \'Department of Critical Care Medicine, The First Affiliated Hospital of Guangxi Medical University, Guangxi, 530021, China.\', \'School of Computer Science and Engineering, South China University of Technology, Guangzhou, 510600, China. hmcai@scut.edu.cn.\']
?:citedBy
  • -1
?:creator
?:doi
  • 10.1007/s12539-020-00408-1
?:doi
?:hasPublicationType
?:journal
  • Interdisciplinary sciences, computational life sciences
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?:pmid
  • 33565027
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  • 0.25
?:rankingScore_hIndex
  • 13
is ?:relation_isRelatedTo_publication of
?:title
  • Classification of COVID-19 by Compressed Chest CT Image through Deep Learning on a Large Patients Cohort.
?:type
?:year
  • 2021

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