Early Detection of Alzheimers Disease using Deep Learning

Abstract

Alzheimer’s disease (AD) poses a significant challenge to global healthcare systems due to its progressive nature and impact on patient’s lives. Accurate and early detection of AD is crucial for timely intervention and management. In this paper, we propose the use of deep learning models, including Convolutional Neural Networks (CNNs), MobileNet, and VGG16 for the classification of Magnetic Resonance Imaging (MRI) scans into different AD stages. Index Terms—Alzheimer’s disease , Deep Learning , Convolu- tional Neural Networks(CNN) , MobileNet , VGG16 , MRI scans