28, May 2026

Machine Learning and Deep Learning Based Detection of Alzheimer’s Disease Using MRI Imaging: A Comprehensive Review

Author(s): Ms. Ankita Shah, Dr. Tejendrakumar Thakur

Authors Affiliations:

1 Assistant Professor, Institute of Advanced Research, Gandhinagar, India

2Assistant Professor, Institute of Advanced Research, Gandhinagar, India

DOIs:10.2015/IJIRMF/202605025     |     Paper ID: IJIRMF202605025


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Abstract: Alzheimer’s Disease (AD) is a progressive neurodegenerative disorder characterized by memory loss, cognitive decline, and behavioral impairment. Early diagnosis is essential for improving treatment outcomes and slowing disease progression. Magnetic Resonance Imaging (MRI) has become one of the most effective imaging modalities for detecting structural brain abnormalities associated with Alzheimer’s Disease. Recent advances in Machine Learning and deep learning have enabled automated analysis of MRI scans for accurate classification of Alzheimer’s stages. This paper presents a comprehensive study of machine learning methods for Alzheimer’s detection using MRI images. The proposed framework includes MRI preprocessing, segmentation, feature extraction, feature selection, and classification using machine learning algorithms such as Support Vector Machine (SVM), Random Forest (RF), K-Nearest Neighbor (KNN), Artificial Neural Networks (ANN), and Convolutional Neural Networks (CNN). Recent research papers are reviewed to analyze existing approaches, datasets, performance metrics, and limitations. Experimental findings from previous studies indicate that deep learning models, especially CNN-based architectures, achieve superior performance in Alzheimer’s classification. The paper also discusses challenges, future directions, and opportunities for multimodal fusion techniques in clinical diagnosis.        
Key Words: Alzheimer’s Disease, MRI, Machine Learning, Deep Learning, CNN, SVM, Medical Imaging

Ms. Ankita Shah, Dr. Tejendrakumar Thakur (2026); Machine Learning and Deep Learning Based Detection of Alzheimer’s Disease Using MRI Imaging: A Comprehensive Review, International Journal for Innovative Research in Multidisciplinary Field, ISSN(O): 2455-0620, Vol-12, Issue-5, Available on –   https://www.ijirmf.com/

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