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is ?:annotates of
?:authorAffiliation
  • [\'Department of Radiology, Shanghai Public Health Clinical Center, Fudan University, Shanghai, China.\', \'Shanghai Key Laboratory of Artificial Intelligence for Medical Image and Knowledge Graph, Shanghai, China.\', \'The SMART (Smart Medicine and AI-based Radiology Technology) Lab, Shanghai Institute for Advanced Communication and Data Science, Shanghai University, Shanghai, China.\', \'School of Communication and Information Engineering, Shanghai University, Shanghai, China.\', \'Institute of Healthcare Research, Yizhi, Shanghai, China.\', \'Shanghai Public Health Clinical Center, Fudan University, Shanghai, China.\', \'Department of Severe Hepatology, Shanghai Public Health Clinical Center, Fudan University, Shanghai, China.\', \'Department of Infectious Disease, Shanghai Public Health Clinical Center, Fudan University, Shanghai, China.\', \'Department of Urology, Shanghai Public Health Clinical Center, Fudan University, Shanghai, China.\']
?:citedBy
  • -1
?:creator
?:doi
?:doi
  • 10.7150/thno.45985
?:hasPublicationType
?:journal
  • Theranostics
is ?:pmid of
?:pmid
?:pmid
  • 32373235
?:publication_isRelatedTo_Disease
?:rankingScore_SJR
  • 2.515
?:rankingScore_hIndex
  • 56
is ?:relation_isRelatedTo_publication of
?:title
  • CT quantification of pneumonia lesions in early days predicts progression to severe illness in a cohort of COVID-19 patients.
?:type
?:year
  • 2020

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