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  • [\'Department of Engineering Science, Institute of Biomedical Engineering, University of Oxford, OX3 7DQ, UK. Electronic address: abhirup.banerjee@cardiov.ox.ac.uk.\', \'School of Mathematics and Statistics, University of Glasgow, Glasgow G12 8QW, UK. Electronic address: Surajit.Ray@glasgow.ac.uk.\', \'School of Mathematics and Physics, University of Lincoln, Brayford Pool, Lincoln LN6 7TS, UK. Electronic address: bvorselaars@lincoln.ac.uk.\', \'School of Computer Science, Electrical and Electronic Engineering, and Engineering Maths, University of Bristol, Merchant Venturers Building, Woodland Rd, Clifton, Bristol BS8 1UB, UK.\', \'School of Computer Science, University of Sheffield, 211 Portobello, Sheffield City Centre, Sheffield S1 4DP, UK.\', \'School of Pharmacy and Biomedical Sciences, University of Brighton, BN2 4GJ, UK.\', \'Hypatia Solutions Ltd, Impact Hub King\'s Cross, 34b York Way, King\'s Cross, London, XGL N1, UK.\', \'School of Pharmacy and Biomedical Sciences, University of Brighton, BN2 4GJ, UK. Electronic address: l.mackenzie2@brighton.ac.uk.\']
?:citedBy
  • -1
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?:doi
  • S1567-5769(20)31577-010.1016/j.intimp.2020.106705
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?:journal
  • International immunopharmacology
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  • 32652499
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  • 1.051
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  • 94
?:title
  • Use of Machine Learning and Artificial Intelligence to predict SARS-CoV-2 infection from Full Blood Counts in a population.
?:type
?:year
  • 2020

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