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is ?:annotates of
?:authorAffiliation
  • [\'Academy for Engineering and Technology, Fudan University, Shanghai, 200433, China.\', \'Department of Radiology, The First Affiliated Hospital of Anhui Medical University, No.218 Jixi Road, Hefei, Anhui, 230022, China.\', \'Shanghai Institute of Medical Imaging, and Department of Interventional Radiology, Zhongshan Hospital, Fudan University, No. 180 Fenglin Road, Xuhui District, Shanghai, 200032, China.\', \'Department of Radiology, Tongde Hospital of Zhejiang Province, Hangzhou, 310012, China.\', \'Department of Radiology, Fuyang Second People\'s Hospital, Fuyang, 236000, China.\', \'The First Affiliated Hospital of Bengbu Medical College, No. 287 Changhuai Road, Bengbu Anhui, 233004, China.\', \'School of Geographic and Biologic Information, Nanjing University of Posts and Telecommunications, Nanjing, 210023, China. shujinzhu@njupt.edu.cn.\', \'The First Affiliated Hospital of Bengbu Medical College, No. 287 Changhuai Road, Bengbu Anhui, 233004, China. zongyuxie@sina.com.\']
?:citedBy
  • -1
?:creator
?:doi
  • 10.1186/s12938-020-00807-x
?:doi
?:hasPublicationType
?:journal
  • Biomedical engineering online
is ?:pmid of
?:pmid
?:pmid
  • 32787937
?:publication_isRelatedTo_Disease
?:rankingScore_SJR
  • 0.542
?:rankingScore_hIndex
  • 58
?:title
  • Rapid identification of COVID-19 severity in CT scans through classification of deep features.
?:type
?:year
  • 2020

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