Prognosis patients with COVID-19 using deep learning.

Journal: BMC medical informatics and decision making
Published Date: Mar 26, 2022

Abstract

BACKGROUND: The coronavirus (COVID-19) is a novel pandemic and recently we do not have enough knowledge about the virus behaviour and key performance indicators (KPIs) to assess the mortality risk forecast. However, using a lot of complex and expensive biomarkers could be impossible for many low budget hospitals. Timely identification of the risk of mortality of COVID-19 patients (RMCPs) is essential to improve hospitals' management systems and resource allocation standards.

Authors

  • José Luis Guadiana-Alvarez
    Escuela de Ingeniería y Ciencias, Tecnologico de Monterrey, Av. Eugenio Garza Sada 2501 Sur, Tecnológico, 64849, Monterrey, N.L., Mexico.
  • Fida Hussain
    Escuela de Ingeniería y Ciencias, Tecnologico de Monterrey, Av. Eugenio Garza Sada 2501 Sur, Tecnológico, 64849, Monterrey, N.L., Mexico. fida.hussain07@yahoo.com.
  • Ruben Morales-Menendez
    Escuela de Ingeniería y Ciencias, Tecnologico de Monterrey, Av. Eugenio Garza Sada 2501 Sur, Tecnológico, 64849, Monterrey, N.L., Mexico.
  • Etna Rojas-Flores
    Escuela de Ingeniería y Ciencias, Tecnologico de Monterrey, Av. Eugenio Garza Sada 2501 Sur, Tecnológico, 64849, Monterrey, N.L., Mexico.
  • Arturo García-Zendejas
    Escuela de Ingeniería y Ciencias, Tecnologico de Monterrey, Av. Eugenio Garza Sada 2501 Sur, Tecnológico, 64849, Monterrey, N.L., Mexico.
  • Carlos A Escobar
    General Motors, Pontiac, MI, USA.
  • Ricardo A Ramirez-Mendoza
    School of Engineering and Science, Tecnologico de Monterrey, Mexico City 14380, Mexico.
  • Jianhong Wang
    School of Electronic Engineering and Automation, Jiangxi University of Science and Technology, Ganzhou, China.

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