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  • [\'Concordia Institute for Information Systems Engineering (CIISE), Concordia University, Montreal, Canada.\', \'Department of Electrical and Computer Engineering, University of Toronto, Toronto, Canada.\', \'Department of Medicine and Diagnostic Radiology, McGill University Health Center-Research Institute, Montreal, QC, Canada.\', \'Department of Electrical and Computer Engineering, Concordia University, Montreal, QC, Canada.\', \'Department of Medical Imaging, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, Canada.\', \'Faculty of Medicine, University of Montreal, Montreal, QC, Canada.\', \'Center for Biomedical Informatics and Information Technology, National Cancer Institute (NCI), Rockville, MD, USA.\', \'Concordia Institute for Information Systems Engineering (CIISE), Concordia University, Montreal, Canada. arash.mohammadi@concordia.ca.\']
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  • -1
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?:doi
  • 10.1038/s41598-022-08796-8
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?:journal
  • Scientific reports
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?:pmid
?:pmid
  • 35318368
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  • 1.533
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  • 122
?:title
  • Human-level COVID-19 diagnosis from low-dose CT scans using a two-stage time-distributed capsule network.
?:type
?:year
  • 2022

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