A regional analysis of COVID-19 in Mexico is presented in this chapter. The populace is more vulnerable to this new pandemic because of comorbidities in Mexican society. The study's time frame is April 12 through October 5, 2020. (761, 665 Patients). In order to analyse the behaviour of patients who tested positive for COVID-19 and their comorbidities, this study's primary goal is to describe a special methodology of random matrix theory in the moments of a probability measure that appears as the limit of the empirical spectral distribution by Wigner's semicircle law. The most sensitive comorbidities in hospitalised patients during the study period are the following: Another goal is to analyse the daily behaviour pandemic; in this chapter, we present the results graphically using Machine Learning techniques and Super Heat maps as a visual aid.
Author(s) Details:
O. Nolasco-Jáuregui,
Department of Biostatistics, Tecana American University, Fort Lauderdale, FL, United States.
L. A. Quezada-Téllez,
Escuela Superior de Apan, Universidad Autónoma del Estado de Hidalgo (UAEH), Chimalpa Tlalayote, Mexico.
Y. Salazar-Flores,
Facultad de Ciencias, Universidad Nacional Autónoma de México, Mexico City, Mexico.
Adán Díaz-Hernández,
Facultad de Economía y Negocios, Universidad Anáhuac México, Huixquilucan, Mexico.
Please see the link here: https://stm.bookpi.org/NRAMCS-V7/article/view/7954
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