Open AccessEarly detection algorithm for alzheimer’s disease using autonomous learning
Author(s) -
Jorge Eduardo Aguilar Obregón,
Octavio José Salcedo Parra,
Juan Pablo Rodríguez Miranda
Publication year - 2021
Publication title -
boletín redipe
Language(s) - English
Resource type - Journals
ISSN - 2256-1536
DOI - 10.36260/rbr.v10i11.1564
Subject(s) - computer science , k nearest neighbors algorithm , neuroimaging , artificial intelligence , disease , process (computing) , machine learning , algorithm , pattern recognition (psychology) , psychology , medicine , neuroscience , pathology , operating system
The current document describes the approach to a research problem that aims to generate an algorithm that allows detecting the probable appearance of Alzheimer’s disease in its first phase, using autonomous learning techniques or Machine Learning, more specifically KNN (K- nearest Neighbor) with which the best result was obtained. This development will be based on a complete information bank taken from ADNI (Alz- heimer’s Disease NeuroImaging Initiative), with all the necessary parameters to direct the inves- tigation to an algorithm that is as efficient as pos- sible, since it has biological, sociodemographic and medical history data, biological specimens, neural images, etc., and in this way the early de- tection of the aforementioned disease was con- figured. A complete guide to the process will be carried out to finally obtain the KNN algorithm whose efficiency is 99%, and then discuss the obtained results.