Early Detection of Alzheimer’s Disease using Machine learning And Neuroimaging Techniques

Author(s)	Mr. Mallela Narasimha Rao, Mr. Avula Vamsi Krishna, Ms. Pattapu Manasa, Ms. Pogula Yamini, Mr. Kavuri Praveen Kumar
Country	India
Abstract	Alzheimer's disease (AD) is the primary cause of amnesia in older adults and is a progressive neurodegenerative disorder associated with cognitive decline and memory loss. Other conditions that can lead to amnesia include Traumatic Brain Injury, Stroke, Encephalitis, and Transient Global Amnesia. Early and accurate diagnosis of AD plays a crucial role. Machine learning techniques have shown great potential in aiding the diagnosis of AD by analyzing large-scale datasets and extracting meaningful patterns and features from the MRI images of brain. The classification of MRI images from the open accessible datasets. Classification of the AD using deep learning and Convolutional Neural Networks (CNN) along with VGG16 algorithm. The system follows various activities like dataset acquisition, image segmentation, feature extraction and classification. The projected arrangement accomplishes noteworthy performance with the finest accuracy. As, the accuracy increases classification will be accurate without any prior errors.
Keywords	Alzheimer’s Disease, Neural Networks, Convolutional Neural Networks, VGG16, MRI images, Deep Learning, Classification
Field	Computer > Data / Information
Published In	Volume 8, Issue 2, March-April 2026
Published On	2026-03-30
DOI	https://doi.org/10.36948/ijfmr.2026.v08i02.72660

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