Predictive Machine Learning Models and Survival Analysis for COVID-19 Prognosis Based on Hematochemi...
Predictive Machine Learning Models and Survival Analysis for COVID-19 Prognosis Based on Hematochemical Parameters
About this item
Full title
Author / Creator
Altini, Nicola , Brunetti, Antonio , Mazzoleni, Stefano , Moncelli, Fabrizio , Zagaria, Ilenia , Prencipe, Berardino , Lorusso, Erika , Buonamico, Enrico , Carpagnano, Giovanna Elisiana , Bavaro, Davide Fiore , Poliseno, Mariacristina , Saracino, Annalisa , Schirinzi, Annalisa , Laterza, Riccardo , Di Serio, Francesca , D'Introno, Alessia , Pesce, Francesco and Bevilacqua, Vitoantonio
Publisher
Switzerland: MDPI AG
Journal title
Language
English
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Publication information
Publisher
Switzerland: MDPI AG
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More information
Scope and Contents
Contents
The coronavirus disease 2019 (COVID-19) pandemic has affected hundreds of millions of individuals and caused millions of deaths worldwide. Predicting the clinical course of the disease is of pivotal importance to manage patients. Several studies have found hematochemical alterations in COVID-19 patients, such as inflammatory markers. We retrospecti...
Alternative Titles
Full title
Predictive Machine Learning Models and Survival Analysis for COVID-19 Prognosis Based on Hematochemical Parameters
Authors, Artists and Contributors
Author / Creator
Brunetti, Antonio
Mazzoleni, Stefano
Moncelli, Fabrizio
Zagaria, Ilenia
Prencipe, Berardino
Lorusso, Erika
Buonamico, Enrico
Carpagnano, Giovanna Elisiana
Bavaro, Davide Fiore
Poliseno, Mariacristina
Saracino, Annalisa
Schirinzi, Annalisa
Laterza, Riccardo
Di Serio, Francesca
D'Introno, Alessia
Pesce, Francesco
Bevilacqua, Vitoantonio
Identifiers
Primary Identifiers
Record Identifier
TN_cdi_doaj_primary_oai_doaj_org_article_9b9ead105b724a1ebd6f52f22910a894
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_9b9ead105b724a1ebd6f52f22910a894
Other Identifiers
ISSN
1424-8220
E-ISSN
1424-8220
DOI
10.3390/s21248503
