Aplicación de redes neuronales para la clasificación de los niveles de tensión arterial en pacientes de Ocaña – Norte de Santander

Karla Yohana Sánchez Mojica; Ariel Fernández Gualdron; Ericson Suarez Gutierrez; José Alejandro Neira Díaz

doi:10.24054/rcta.v1i41.2415

Authors

Karla Yohana Sánchez Mojica Corporación Universitaria Iberoamericana https://orcid.org/0000-0003-3164-4725
Ariel Fernández Gualdron Corporación Universitaria Iberoamericana https://orcid.org/0009-0009-2177-1019
Ericson Suarez Gutierrez Corporación Universitaria Iberoamericana https://orcid.org/0009-0007-5756-9678
José Alejandro Neira Díaz Corporación Universitaria Iberoamericana https://orcid.org/0000-0002-4503-6301

DOI:

https://doi.org/10.24054/rcta.v1i41.2415

Keywords:

Model, Neuron, Level, Network, Voltage

Abstract

The objective of this research is to model the behavior of blood pressure taking into account two factors such as age and gender in patients from the city of Ocaña - Norte de Santander. For the development of the project, the fundamental stages of data analysis are taken into account: adaptation of the database, exploratory analysis, verification of artificial intelligence models with classifying neural networks; the nature of the research is exploratory with a quantitative approach and non-experimental design. Various neural network models with different numbers of hidden layers and number of neurons were tested; it was found that the model with the highest precision was with two hidden layers of 100 neurons each, which achieved an accuracy of 87%. In conclusion, it was possible to determine a model of neural networks that, with the characteristics of gender and age, plus diastolic and systolic pressure, can classify the patient in the levels hypotension, hypertension, normal, optimal, systolic hypertension or detect any abnormality.

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