Clasificación de pacientes con síntomas de COVID-19 mediante árboles de decisión como una aplicación del aprendizaje automático

Julio Enrique Trujillo González; Carolina Vejerano García

doi:10.48204/j.guacamaya.v8n1.a4319

Submitted October 3, 2023

Published 2023-10-09

Artículos

Vol. 8 No. 1 (2023): Revista Científica Guacamaya

Classification of patients with COVID-19 symptoms using decision trees as an application of machine learning

Julio Enrique Trujillo González⁺⁻
Carolina Vejerano García⁺⁻

DOI https://doi.org/10.48204/j.guacamaya.v8n1.a4319

PDF (Español (España))

References

DOI: 10.48204/j.guacamaya.v8n1.a4319

Published: 2023-10-09

How to Cite

Trujillo González, J. E., & Vejerano García, C. (2023). Classification of patients with COVID-19 symptoms using decision trees as an application of machine learning. Revista Científica Guacamaya, 8(1), 79–85. https://doi.org/10.48204/j.guacamaya.v8n1.a4319

This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.

Abstract

The objective of this work was to classify patients with symptoms of COVID-19 using decision trees. Where the sklearn package was very useful to obtain the model, its graphic representation and the most important variables. The model allows us to classify 74.78% of patients with symptoms.

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