Abstract

Abstract - Alzheimer disease is one of the most common and fastest growing neuro degenerative diseases in the western countries. Development of different biomarkers tools are key issues for diagnosis of Alzheimer disease and its progression.The aim of this paper is making use of machine learning algorithms to process this data obtained by neuroimaging technologies for detection of Alzheimer’s in its primitive stage. Machine learning is being widely used in various medical fields. Advances in medical technologies have given access to better data for identifying symptoms of variousdiseases in early stages. Alzheimer’s disease is a chronic condition that leads to degeneration of brain cells leading to memory enervation. Patients with cognitive mental problems such as confusion and forgetfulness, also other symptoms including behavioral and psychological problems are further suggested having CT, MRI, PET, EEG, and other neuroimaging techniques.