Prevention of obesity using Hopfield networks in patients with obese ancestry.

Authors

  • Mariel Abigail Cruz Nájera Universidad Autonoma de Tamaulipas
  • Julio Laria Mechaca
  • Salvador Ibarra Martínez
  • Jesús David Terán Villanueva
  • Daniel Adalberto Martínez Vega

Keywords:

Obesity, Cardiovascular Diseases

Abstract

Abstract. This paper proposes a risk study to suffer from obesity based on genetics and caloric intake. Using the calculation of the amount of glucose ingested and Hopfield networks to detect patterns of kinship between a control group and their relatives with obesity or bad eating habits. Of the volunteers who are at risk of triggering obesity, 43% have good nutrition and obese parents, another 43% have a poor diet with obese parents, those volunteers who have poor nutrition and do not have overweight parents, have a 10% risk of obesity, those who do not have obese parents and have poor nutrition, their risk percentage is 4%. It was possible to detect the predominance of genetics in obesity and the advantages of the use of computer techniques in the support for the timely detection of obesity.

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Published

2020-01-02

How to Cite

Cruz Nájera, M. A., Laria Mechaca, J., Ibarra Martínez, S., Terán Villanueva, J. D., & Martínez Vega, D. A. (2020). Prevention of obesity using Hopfield networks in patients with obese ancestry. International Journal of Combinatorial Optimization Problems and Informatics, 11(2), 61–66. Retrieved from https://ijcopi.org/ojs/article/view/144

Issue

Vol. 11 No. 2 (2020)

Section

Articles

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