Analysis of Cognitive Emotional and Behavioral Aspects of Alzheimer's Disease Using Hybrid CNN Model

Abstract

Alzheimer's disease is a brain related disorder which occurs by the growth upon unnecessary growth of protein in and around the brain cells. This disease causes memory loss in the human that makes them do activities slowly and repeatedly. The patients who suffer the disease couldn't handle the money properly, they repeat the questions often and they suffer challenges in planning. To some extent it makes the interactions with the environment complicated. Being a cruel disease, this should be analyzed and treated in the initial state. Thus, predicting disease is essential. This paper explains how machine learning algorithms helps patients to get predicted and classified on Alzheimer's disease. The algorithms used in the papers includes VGG-16, DENSENET-121, CNN. As it is a hybrid model, the efficiencies of the algorithms are compared and found an efficient result at the end of the research.