Alzheimer Disease Classification Model Using Machine Learning Techniques

Abstract

Technological advances have allowed the machine learning area of the field of artificial intelligence to emerge and provide new solutions to different problems. Medicine is one of the sciences driving these advanced solutions. Using real-time data, a model has been developed for the classification of brain images taken through neuroimaging techniques to assist in the diagnosis of Alzheimer's disease (AD). Alzheimer's is a very important condition as it affects cognitive functions and daily living activities. For the development of this work, convo-lutional neural networks were used with a total of 5,600 images for training and testing; the images were extracted from medical reports. In the end, an accuracy level of 70% was reached in all cases during training and evaluation. This percentage was considered acceptable by the medical specialist.