Several risk factors have been identified to predict worse outcomes in patients affected by SARS-CoV-2 infection. Machine learning algorithms represent a novel approach to identifying a prediction model with a good discriminatory capacity to be easily used in clinical practice. The aim of this study was to obtain a risk score for in-hospital mortality in patients with coronavirus disease infection (COVID-19) based on a limited number of features collected at hospital admission.

Machine learning for prediction of in-hospital mortality in coronavirus disease 2019 patients: results from an Italian multicenter study

Vezzoli, Marika;Inciardi, Riccardo Maria;Oriecuia, Chiara;Paris, Sara;Murillo, Natalia Herrera;Carubelli, Valentina;Guazzi, Marco;Maccagni, Gloria;Mapelli, Massimo;Pagnesi, Matteo;Sinagra, Gianfranco;Tomasoni, Daniela;Adamo, Marianna;Maroldi, Roberto;Metra, Marco;Lombardi, Carlo Mario
;
Specchia, Claudia
2022-01-01

Abstract

Several risk factors have been identified to predict worse outcomes in patients affected by SARS-CoV-2 infection. Machine learning algorithms represent a novel approach to identifying a prediction model with a good discriminatory capacity to be easily used in clinical practice. The aim of this study was to obtain a risk score for in-hospital mortality in patients with coronavirus disease infection (COVID-19) based on a limited number of features collected at hospital admission.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11379/559755
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