COVID-19 mortality risk assessments for individuals with and without diabetes mellitus : machine learning models integrated with interpretation framework

Khadem, H. orcid.org/0000-0002-6878-875X, Nemat, H., Eissa, M.R. orcid.org/0000-0002-5584-5815 et al. (2 more authors) (2022) COVID-19 mortality risk assessments for individuals with and without diabetes mellitus : machine learning models integrated with interpretation framework. Computers in Biology and Medicine, 144. 105361. ISSN 0010-4825

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Item Type: Article
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© 2022 Elsevier Ltd. This is an author produced version of a paper subsequently published in Computers in Biology and Medicine. Uploaded in accordance with the publisher's self-archiving policy. Article available under the terms of the CC-BY-NC-ND licence (https://creativecommons.org/licenses/by-nc-nd/4.0/).

Keywords: Machine learning; COVID-19; Diabetes mellitus; Risk assessment; Model interpretation
Dates:
  • Published: May 2022
  • Published (online): 2 March 2022
  • Accepted: 26 February 2022
Institution: The University of Sheffield
Academic Units: The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Electronic and Electrical Engineering (Sheffield)
The University of Sheffield > Sheffield Teaching Hospitals
Depositing User: Symplectic Sheffield
Date Deposited: 07 Mar 2022 08:17
Last Modified: 02 Mar 2023 01:13
Status: Published
Publisher: Elsevier BV
Refereed: Yes
Identification Number: 10.1016/j.compbiomed.2022.105361
Open Archives Initiative ID (OAI ID):

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