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

Merlo, Marco;Nuzzi, Vincenzo;Sinagra, Gianfranco;
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.
2022
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https://journals.lww.com/jcardiovascularmedicine/Fulltext/2022/07000/Machine_learning_for_prediction_of_in_hospital.4.aspx#ej-article-sam-container
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11368/3038979
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