Opti-MuDR_CNN: An Enhanced Approach for Classification of Early Onset of Alzheimer’s Disease

Opti-MuDR_CNN: An Enhanced Approach for Classification of Early Onset of Alzheimer’s Disease

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© 2024 by IJETT Journal
Volume-72 Issue-5
Year of Publication : 2024
Author : Afiya Parveen Begum, Prabha Selvaraj
DOI : 10.14445/22315381/IJETT-V72I5P127

How to Cite?

Afiya Parveen Begum, Prabha Selvaraj, "Opti-MuDR_CNN: An Enhanced Approach for Classification of Early Onset of Alzheimer’s Disease," International Journal of Engineering Trends and Technology, vol. 72, no. 5, pp. 261-274, 2024. Crossref, https://doi.org/10.14445/22315381/IJETT-V72I5P127

Abstract
Alzheimer’s Disease (AD) is commonly found in aged people and adults. This kind of disease is predicted using various hybrid methods, such as a combination of Machine Learning (ML) and Deep Learning (DL) in the medical field. Therefore, image classification problems are considered a significant limitation of the existing research and the current scenario. In Current research, a novel technique - Opti Multi Hidden Deep rooted Convolutional Neural Network has been utilized to classify the early onset of AD. In our work, we have given the segmented images to different architectures like EfficientnetB7, Restnet50, and Opti Multi hidden deep-rooted CNN, where our proposed model Opti Multi hidden Deep rooted CNN model has achieved the best accuracy. The proposed method Opti Multi Hidden Deep rooted Convolutional Neural Network has been compared in terms of certain performance measures like MAP - Mean-Average-Precision, F1- score, recall, precision, and accuracy with the existing methods like ResNet50 and EfficientNetB7 and obtained the best results than existing methods. Eventually, the proposed approach achieved more efficient results compared to the other existing methods. In the future, large real-time datasets will be used with the integration of the proposed system to enhance accuracy and sensitivity.

Keywords
Alzheimer’s Disease (AD), MRI, Convolutional Neural Network (CNN), Dwarf Mongoose Optimization Algorithm (DMOA), Deep Learning (DL).

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