Alzheimer’s disease Detection through Machine Learning

Abstract

A neurological disease Alzheimer's disease (AD) that occurs most commonly in older adults and is a common reason for dementia. The accurate and timely diagnosis of Alzheimer's disease is important to prevent it from spreading at an irreversible level. This paper concentrates on a machine learning method used to identify Alzheimer's from magnetic resonance images. The proposed approach will focus on the purposeful area of the hippocampus ROI boundary. The HC ROIBR features such as entropy, variance, contrast, energy, and correlation are computed. Our proposed method for classification of AD into stages such as normal, mild, moderate, and severe, use neural network and  support vector machine.