EARLY STAGE ALZHEIMER'S DISEASE DIAGNOSIS METHOD

The Alzheimer's disease accurate early-stage detection is critically necessary for effective treatment and recovery. Therefore, accurate detection of Alzheimer's disease is a great research problem. Different researchers used various techniques to detect Alzheimer's disease effectively however; these methods still have lack of prediction accuracy. In this study we proposed machine learning-based method to diagnosis Alzheimer's disease accurately. We used machine learning classifiers for accurate prediction of Alzheimer's disease. Alzheimer's Disease Neuroimaging Initiative data set has been used to check the proposed method performance. The experimental results demonstrate that logistic regression performance was excellent in terms of accuracy and achieved optimal accuracy 98.12%.Thus, it is recommended for effective early detection of Alzheimer's Disease.