Prediction of Alzheimer's disease using Machine Learning Algorithm

Abstract

Alzheimer's disease has recently become a big worry. This condition affects around 45 million individuals worldwide. Alzheimer is a degenerative mind illness that typically affects elderly adults and has no known aetiology or pathophysiology. Dementia is the essential cause of Alzheimer's infection, which kills synapses over the long haul. This ailment removed individuals' ability to think, read, and do numerous different things. By guagzing the disorder, an AI framework can assist with taking care of this issue. The major goal is to identify Dementia in a variety of individuals. This study offers the results and analyses of multiple machine learning models for diagnosing dementia. For development of system OASIS's dataset used. Although the dataset is modest, it contains some significant numbers. The data was examined and used two machine learning models. For prediction, support vector machines and random forests were employed. After system development and results shows SVM gives better performance than other model. Result shows comparison of RF and SVM based on accuracy and F1 Score. The approach is straightforward and can quickly assist individuals in recognizing Dementia