Modelo de predicción temprana de diabetes aplicando Machine Learnin

Abstract

Abstract: Diabetes mellitus is the second cause of death in the country, it is a illness that affects Ecuadorian citizens progressiveness with great speed, currently one in ten persons has been diagnosed with this disease. There are many risk factors that cannot be changed: genetic, gender, etnic, to name a few; and others than can be modified: diet, sedentary lifestyle, alcohol and tobacco use, all of them related to this disease. These last factors are we should improve as a precautionary measure. In this work of curriculum integration are presented some supervised learning methodologies of Machine Learning, based on classification algorithms, for analyzing, processing and interpreting data; to determine which one is more accurate. This allows to generate a diabetes early prediction model, that can be use to determine before time if a person is prone to this disease, using some variables that allow analyzing and compare obtained results; and in this way be part of the secondary prevention of diabete.