Deep Learning-Based Alzheimer’s Disease Detection: A CNN Approach

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This is an unedited manuscript accepted for publication and provided as an Article in Press for early access at the author’s request. The article will undergo copyediting, typesetting, and galley proof review before final publication. Please be aware that errors may be identified during production that could affect the content. All legal disclaimers of the journal apply.

Year : 2025 | Volume : 15 | Issue : 03 | Page :
    By

    Malik Hyder Ali,

  • Harsh Kumar,

  1. Assistant Professor, Department Computer Science and Engineering Akal University, Talwandi Sabo, India
  2. Researcher, Department of Computer Science and Engineering, Akal University Talwandi Sabo, India

Abstract

Alzheimer’s disease (AD) is a neurological condition that worsens with time and impairs a patient’s quality of life by causing cognitive loss. For prompt intervention and management of AD, early identification is essential. In this work, we propose a deep learning-based method for automatically classifying Alzheimer’s disease from medical imaging data using convolutional neural networks (CNNs). Our algorithm is intended to evaluate brain MRI images and detect anatomical variations suggestive of AD. The CNN architecture is designed to discriminate between people who are healthy, those who have mild cognitive impairment, and people who have Alzheimer’s disease with high accuracy and robustness. The model demonstrated noteworthy performance in terms of accuracy, sensitivity, and specificity when it was trained on a dataset of MRI scans. According to our findings, CNN-based models present a viable means of diagnosing Alzheimer’s disease early and precisely, which can help doctors decide on the best course of treatment. This work demonstrates the promise of deep learning for neuroimaging and its use in diagnosing neurodegenerative diseases.

Keywords: Alzheimer’s disease, Convolutional Neural Networks, deep learning, MRI, neuroimaging, early diagnosis, medical image analysis, mild cognitive impairment, automatic classification, neurodegenerative disorders

[This article belongs to Research and Reviews: A Journal of Neuroscience ]

How to cite this article:
Malik Hyder Ali, Harsh Kumar. Deep Learning-Based Alzheimer’s Disease Detection: A CNN Approach. Research and Reviews: A Journal of Neuroscience. 2025; 15(03):-.
How to cite this URL:
Malik Hyder Ali, Harsh Kumar. Deep Learning-Based Alzheimer’s Disease Detection: A CNN Approach. Research and Reviews: A Journal of Neuroscience. 2025; 15(03):-. Available from: https://journals.stmjournals.com/rrjons/article=2025/view=232950


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Regular Issue Subscription Original Research
Volume 15
Issue 03
Received 27/05/2025
Accepted 14/07/2025
Published 25/11/2025
Publication Time 182 Days
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