Identifying Alzheimer Disease Dementia Levels Using Machine Learning Methods

Dementia, a prevalent neurodegenerative condition, is major manifestation of Alzheimer's disease (AD). As the condition progresses from mild to severe, it significantly impairs individual's ability perform daily tasks independently, necessitating need for timely and accurate AD classification. Machine learning or deep models have emerged as effective tools this purpose. In study, we suggested an approach classifying four stages dementia using RF, SVM, CNN algorithms, augmented with watershed segmentation feature extraction MRI images. Our results reveal that SVM features achieves impressive accuracy 96.25%, surpassing other classification methods. The ADNI dataset utilized evaluate effectiveness our method, observed inclusion contributes enhanced performance models.