Detection and Prediction of Alzheimer’s Disease Using Rule Induction Method

The primary reason for dementia, which commonly affects older persons, is Alzheimer’s disease. Particularly when it comes to treatment, this illness is expensive. Alzheimer’s disease is also one of the leading causes of mortality for senior individuals. Early Alzheimer’s detection aids in the diagnosis of the illness by medical professionals, hence reducing the danger of death. As a result, early Alzheimer's disease identification has turned into a major issue in the medical field. This research study aims to present a machine learning-based computer-aided diagnosis method for Alzheimer’s disease detection. We used brain datasets from the Open Access Series of Imaging Studies (OASIS) and the Alzheimer’s Disease Neuroimaging Initiative (ADNI). Some supervised machine learning methodologies, including logistic regression, support vector machines, random forests, linear discriminant analysis, and rule induction method (RIM), have been used to guess Alzheimer’s disease.