Modelo computacional de clasificación de aprendizaje de máquina supervisado, para el análisis de datos cardiovas-culares y pronóstico médico

Abstract:

Cardiovascular diseases are a public health problem in Ecuador and around the world, so this research work proposes the design of a computational model of classification using techniques of machine Learning, with the support of probabilistic models that allow modeling of cardiovascular disease risk factors. This model is based on Bayesian Networks, which, based on the risk factors of the disease, will show the percentage that the patient has of contracting it. The documentary research methodology was applied that provides the necessary knowledge to carry out this project in which tests were carried out to verify the behavior of each of the variables used in the probabilistic model, which will provide efficient results. and in a short period of time, thus being a support tool in decision-making for experts.

Año de publicación:

2020

Keywords:

Fuente:

google