IJETEV1I1A010 – EARLY DETECTION OF ALZHEIMER’S DISEASE FROM BRAIN MRI USING VGG16 – BASED DEEP LEARNING

ABSTRACT – Alzheimer’s disease (AD) is a progressive neurodegenerative disorder that leads to memory loss and cognitive decline. Early diagnosis is essential for effective disease management and improved patient outcomes. This paper presents an automated deep learning-based approach for early detection of Alzheimer’s disease using brain MRI images and a VGG16-based convolutional neural network. Transfer learning is employed to finetune the pre-trained VGG16 model for identifying disease-specific patterns in MRI scans. Image normalization and data augmentation are applied to enhance model performance and generalization. Experimental results show that the proposed model achieves high accuracy while reducing reliance on manual diagnosis, making it a reliable and scalable tool for clinical decision support.