A Machine Learning Model for Predicting Hospitalization in Patients with Respiratory Symptoms during the COVID-19 Pandemic

A machine learning approach is a useful tool for risk-stratifying patients with respiratory symptoms during the COVID-19 pandemic, as it is still evolving. We aimed to verify the predictive capacity of a gradient boosting decision trees (XGboost) algorithm to select the most important predictors inc...

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Detalles Bibliográficos
Autores principales: De Freitas, Victor Muniz, Chiloff, Daniela Mendes, Bosso, Giulia Gabriella, Teixeira, Janaina Oliveira Pires, Hernandes, Isabele Cristina de Godói, Padilha, Maira do Patrocínio, Moura, Giovanna Corrêa, De Andrade, Luis Gustavo Modelli, Mancuso, Frederico, Finamor, Francisco Estivallet, Serodio, Aluísio Marçal de Barros, Arakaki, Jaquelina Sonoe Ota, Sartori, Marair Gracio Ferreira, Ferreira, Paulo Roberto Abrão, Rangel, Érika Bevilaqua
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9369854/
https://www.ncbi.nlm.nih.gov/pubmed/35956189
http://dx.doi.org/10.3390/jcm11154574

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9369854/
https://www.ncbi.nlm.nih.gov/pubmed/35956189
http://dx.doi.org/10.3390/jcm11154574

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