Recognizing Patterns on Two Principal Causes of Death in the Mexican Population during the Period 2010-2021

Two of the 11 primary causes of death among the Mexican population during the period 2010-2021 were analyzed in its correlation with Mexico's socio-economic situation and the identified patterns are presented. It has been confirmed that the application of learning algorithms, specifically the use of decision trees, is very useful in analyzing and correlating data from various sources, which is evidenced by the obtained results. The constructed decision trees illustrate and explain the patterns found between deaths from heart disease and suicide compared to certain socio-economic attributes from Mexico. This helps to characterize the population that experienced these deaths. Our results can be utilized to aid in the decision-making process for policies aimed at preventing health issues that affect the Mexican population, as well as to define other health public policies.

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Publication Details

Journal
Journal of Scientometric Research
Published
2025-03-27
DOI
https://doi.org/10.5530/jscires.20251454
Primary Topic
Healthcare Systems and Reforms
Type
article
Field-Weighted Citation Impact
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article

Recognizing Patterns on Two Principal Causes of Death in the Mexican Population during the Period 2010-2021

Guillermo De Ita Luna, Daniel Varela, Eduardo Barragán
Journal of Scientometric Research
Healthcare Systems and Reforms
article

Recognizing Patterns on Two Principal Causes of Death in the Mexican Population during the Period 2010-2021

Guillermo De Ita Luna, Daniel Varela, Eduardo Barragán
article en

Abstract

Two of the 11 primary causes of death among the Mexican population during the period 2010-2021 were analyzed in its correlation with Mexico's socio-economic situation and the identified patterns are presented. It has been confirmed that the application of learning algorithms, specifically the use of decision trees, is very useful in analyzing and correlating data from various sources, which is evidenced by the obtained results. The constructed decision trees illustrate and explain the patterns found between deaths from heart disease and suicide compared to certain socio-economic attributes from Mexico. This helps to characterize the population that experienced these deaths. Our results can be utilized to aid in the decision-making process for policies aimed at preventing health issues that affect the Mexican population, as well as to define other health public policies.

Journal of Scientometric ResearchVol. 14(1)
Universidad Popular Autónoma del Estado de Puebla (MX), Benemérita Universidad Autónoma de Puebla (MX)
Openalex Percentile: Top 92%
Healthcare Systems and Reforms
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