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is ?:annotates of
?:authorAffiliation
  • [\'School of Management & Enterprise, University of Southern Queensland, Toowoomba 2550, Australia.\', \'Department of Biomedical Imaging, Faculty of Medicine, University of Malaya, Kuala Lumpur 50603, Malaysia.\', \'Department of Pulmonology Clinic, Firat University Hospital, Firat University, Elazig 23119, Turkey.\', \'Department of Digital Forensics Engineering, College of Technology, Firat University, Elazig 23119, Turkey.\', \'Department of Computer Engineering, College of Engineering, Ardahan University, Ardahan 75000, Turkey.\', \'Science, Mathematics and Technology Cluster, Singapore University of Technology and Design, 8 Somapah Road, Singapore S485998, Singapore.\', \'Department of Electronics and Computer Engineering, Ngee Ann Polytechnic, Singapore S599489, Singapore.\', \'Department of Biomedical Engineering, School of Science and Technology, Singapore University of Social Sciences, Singapore S599494, Singapore.\', \'Department of Biomedical Informatics and Medical Engineering, Asia University, Taichung 41354, Taiwan.\']
?:citedBy
  • -1
?:creator
?:doi
?:doi
  • 805210.3390/ijerph18158052
?:hasPublicationType
?:journal
  • International journal of environmental research and public health
is ?:pmid of
?:pmid
?:pmid
  • 34360343
?:publication_isRelatedTo_Disease
?:rankingScore_SJR
  • 0.735
?:rankingScore_hIndex
  • 67
is ?:relation_isRelatedTo_publication of
?:title
  • Automatic COVID-19 Detection Using Exemplar Hybrid Deep Features with X-ray Images.
?:type
?:year
  • 2021

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