Use of machine learning and artificial intelligence to predict SARS-CoV-2 infection from full blood counts in a population

Banerjee, A., Ray, S., Vorselaars, B. et al. (5 more authors) (2020) Use of machine learning and artificial intelligence to predict SARS-CoV-2 infection from full blood counts in a population. International Immunopharmacology, 86. 106705. ISSN 1567-5769

Abstract

Metadata

Authors/Creators:
Copyright, Publisher and Additional Information: © 2020 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/BY-NC-ND/4.0/).
Keywords: SARS-CoV-2; Machine Learning; Artificial Neural Network (ANN); Screening; Full blood count; Leukocytes; Monocytes
Dates:
  • Accepted: 11 June 2020
  • Published (online): 16 June 2020
  • Published: September 2020
Institution: The University of Sheffield
Academic Units: The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Computer Science (Sheffield)
Depositing User: Symplectic Sheffield
Date Deposited: 17 Jul 2020 13:43
Last Modified: 17 Jul 2020 13:43
Status: Published
Publisher: Elsevier BV
Refereed: Yes
Identification Number: https://doi.org/10.1016/j.intimp.2020.106705

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