Please use this identifier to cite or link to this item:
https://dspace.univ-ouargla.dz/jspui/handle/123456789/34489
Title: | Efficient Image Classification for Early Prediction of Alzheimer's Disease |
Authors: | BENKADDOUR, Mohammed Kamel Bendehiba, Kaouthar Habita, Atidel |
Keywords: | Alzheimer’s Disease Brain Deep learning Medical Image MRI CNN Dataset Prediction |
Issue Date: | 2023 |
Publisher: | Kasdi Marbah University Ouargla |
Abstract: | Alzheimer’s disease is a type of brain disease. It is a progressive disease which means it gets worse with time there is no cure and his diagnosis is a medical challenge. Therefore, early diagnosis is crucial and can help to improve symptoms significantly. As technology advances, deep learning techniques have recently achieved great success in medical image analysis. This project aims to develop a method of Alzheimer's disease diagnosis using MRI images, which can distinguish medical images of the brain to help doctors to classify and predict Alzheimer's disease. This is based on deep learning with convolutional neural networks (CNN) used to predict Alzheimer from the Kaggle dataset. Experiments results have given encouraging prediction and accuracy in comparison with other work cited in related works. |
URI: | https://dspace.univ-ouargla.dz/jspui/handle/123456789/34489 |
Appears in Collections: | Département d'informatique et technologie de l'information - Master |
Files in This Item:
File | Description | Size | Format | |
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BENDEHIBA-HABITA.pdf | 4,97 MB | Adobe PDF | View/Open |
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