Determining the Influence of Socioeconomic and Clinical Factors in Diabetes in the Mexican Population Using Machine Learning Techniques
Journal
Machine Learning Methods in Biomedical Field : Computer-Aided Diagnostics, Healthcare and Biology Applications
ISSN
1860-949X
1860-9503
Publisher
Springer Nature Switzerland
Date Issued
2025
Type
text::book::book part
Abstract
Diabetes has a significant cost for health systems and the economy in general of countries, in addition to affecting the quality of life of people who suffer from it. Studying and analyzing the economic and clinical factors that trigger it allows us to identify the financial burden it represents and how policies and programs can be generated to support the prevention of this disease. This research aims to analyze the influence of socioeconomic and clinical factors on the Mexican population suffering from Diabetes. The analysis methods that are applied are the machine learning technique. The results in the Mexican population show that deaths from Diabetes occur more frequently in the population between 20 and 59 years of age. The factors related to housing-urbanization, specifically homes without piped water homes and houses with dirt floors, as well as people without the right to social security, are the critical factors that correlate with deaths caused by Diabetes: Hypertension, pneumonia, chronic respiratory diseases, coronary diseases, and influenza. ©The authors © Springer.
License
Acceso Restringido
How to cite
Martínez-Velasco, A., Terán-Bustamante, A. (2026). Determining the Influence of Socioeconomic and Clinical Factors in Diabetes in the Mexican Population Using Machine Learning Techniques. In: Moya-Albor, E., Ponce, H., Brieva, J., Gomez-Coronel, S.L., Torres, D.R. (eds) Machine Learning Methods in Biomedical Field. Studies in Computational Intelligence, vol 1218. Springer, Cham. https://doi.org/10.1007/978-3-031-96328-5_14