Behavioral analysis of medical data COVID -19 through artificial intelligence

Authors

  • Antonio Álvarez Núñez Benemérita Universidad Autónoma de Puebla, Facultad de Ciencias de la Computación
  • María del Carmen Santiago Díaz Benemérita Universidad Autónoma de Puebla, Facultad de Ciencias de la Computación
  • Ana Claudia Zenteno Vázquez Benemérita Universidad Autónoma de Puebla, Facultad de Ciencias de la Computación
  • Judith Pérez Marcial Benemérita Universidad Autónoma de Puebla, Facultad de Ciencias de la Computación
  • Gustavo Trinidad Rubín Linares Benemérita Universidad Autónoma de Puebla, Facultad de Ciencias de la Computación

DOI:

https://doi.org/10.61467/2007.1558.2024.v15i5.580

Keywords:

Artificial Intelligence, Multiple Choice and Decision Tree

Abstract

The COVID-19 pandemic has generated a global health crisis, and having tools that allow the disease to be efficiently managed is of vital importance. In this context, artificial intelligence offers a unique opportunity to analyze large volumes of medical data and obtain valuable information that can contribute to medical decision-making and improve management of the pandemic. In this work, artificial intelligence techniques are applied to model the results obtained from COVID-19 databases in Mexico.

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Published

2024-11-29

How to Cite

Álvarez Núñez, A. ., Santiago Díaz, M. del C., Zenteno Vázquez, A. C., Pérez Marcial, J., & Rubín Linares, G. T. (2024). Behavioral analysis of medical data COVID -19 through artificial intelligence . International Journal of Combinatorial Optimization Problems and Informatics, 15(5), 212–217. https://doi.org/10.61467/2007.1558.2024.v15i5.580

Issue

Vol. 15 No. 5 (2024)

Section

Articles

License

Copyright (c) 2024 International Journal of Combinatorial Optimization Problems and Informatics

Creative Commons License

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

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