Please use this identifier to cite or link to this item: https://dspace.univ-ouargla.dz/jspui/handle/123456789/34489
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dc.contributor.authorBENKADDOUR, Mohammed Kamel-
dc.contributor.authorBendehiba, Kaouthar-
dc.contributor.authorHabita, Atidel-
dc.date.accessioned2023-10-03T10:35:09Z-
dc.date.available2023-10-03T10:35:09Z-
dc.date.issued2023-
dc.identifier.urihttps://dspace.univ-ouargla.dz/jspui/handle/123456789/34489-
dc.description.abstractAlzheimer’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.en_US
dc.language.isoenen_US
dc.publisherKasdi Marbah University Ouarglaen_US
dc.subjectAlzheimer’s Diseaseen_US
dc.subjectBrainen_US
dc.subjectDeep learningen_US
dc.subjectMedical Imageen_US
dc.subjectMRIen_US
dc.subjectCNNen_US
dc.subjectDataseten_US
dc.subjectPredictionen_US
dc.titleEfficient Image Classification for Early Prediction of Alzheimer's Diseaseen_US
dc.typeThesisen_US
Appears in Collections:Département d'informatique et technologie de l'information - Master

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