Machine learning for COVID-19 mortality prediction: enhancing cart models with node-specific odds ratios

Machine learning for COVID-19 mortality prediction: enhancing cart models with node-specific odds ratios

Argelia Pérez-Pacheco 1, Alejandra E. Herrera-Suárez 2, Jonathan Vélez-Mata 2, Liza M. Magdaleno-Fourlong 2, Amy D. Avendaño-Carrera 2, Catalina Casillas-Suárez 3, Adolfo Pérez-García 4

1 Research and Technological Development Unit; Department of Research. Hospital General de Mexico ???Dr. Eduardo Liceaga???, Mexico City, Mexico; 2 Research and Technological Development Unit, Hospital General de Mexico ???Dr. Eduardo Liceaga???, Mexico City, Mexico; 3 Pulmonology Service, Hospital General de Mexico ???Dr. Eduardo Liceaga???, Mexico City, Mexico; 4 Department of Research, Hospital General de Mexico ???Dr. Eduardo Liceaga???, Mexico City, Mexico

Argelia Pérez-Pacheco, Alejandra E. Herrera-Suárez, Jonathan Vélez-Mata, Liza M. Magdaleno-Fourlong, Amy D. Avendaño-Carrera, Catalina Casillas-Suárez, Adolfo Pérez-García

La información completa de afiliaciones y autor de correspondencia está disponible en la versión original en PDF.

*Correspondence: Adolfo Pérez-García. Email: adolfo.perez@salud.gob.mx

Abstract

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Keywords:  COVID-19. Mortality prediction. Classification and regression tree model. Mechanical ventilation. Machine learning. Odds ratio.

Contents

⇄ Versión en Español
DOI: 10.24875/CIRUE.M25000948
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    DOI: 10.24875/CIRUE.M25000948