Deep learning prediction of likelihood of ICU admission and mortality in COVID-19 patients using cli...
Deep learning prediction of likelihood of ICU admission and mortality in COVID-19 patients using clinical variables
About this item
Full title
Author / Creator
Publisher
United States: PeerJ. Ltd
Journal title
Language
English
Formats
Publication information
Publisher
United States: PeerJ. Ltd
Subjects
More information
Scope and Contents
Contents
This study aimed to develop a deep-learning model and a risk-score system using clinical variables to predict intensive care unit (ICU) admission and in-hospital mortality in COVID-19 patients.
This retrospective study consisted of 5,766 persons-under-investigation for COVID-19 between 7 February 2020 and 4 May 2020. Demographics, chronic comorb...
Alternative Titles
Full title
Deep learning prediction of likelihood of ICU admission and mortality in COVID-19 patients using clinical variables
Authors, Artists and Contributors
Identifiers
Primary Identifiers
Record Identifier
TN_cdi_doaj_primary_oai_doaj_org_article_b8991c5d7f0545b6854456af7fa8b5a9
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_b8991c5d7f0545b6854456af7fa8b5a9
Other Identifiers
ISSN
2167-8359
E-ISSN
2167-8359
DOI
10.7717/peerj.10337
