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Multiclass-classification of Alzheimer‟s Disease using 3-D CNN and Hyper-Parameter Optimization of Machine Learning Algorithms
Published in International Journal of Science and Research (IJSR)
Volume: 9.0
Issue: 3.0
Pages: 1035.0 - 1040.0
Dementia and its forms like Mild Cognitive Impairment and Alzheimer’s Disease are posing great defiance to societyclaiming many lives. Alzheimer’s Disease is the fifth leading cause of death in the world. The most frequently observed form of thisdementia is Alzheimer’s Disease. Diagnosis of this disease is a very tedious task for the doctors, which can lead to errors in thejudgment. This paper proposes multi-class classification by using MRI Images of subjects into 3 different classes such as Normal, MCI(Mild Cognitive Impairment) and Alzheimer’s Disease. The presented 3D CNN model can accurately classify Cognitive Normal patientsand also MCI (Mild Cognitive Impairment) which may morph into Alzheimer’s Disease to prevent the further disintegration andseverity of the patient’s condition. This paper also presents the comparative study of the performance of different Machine Learningmodels on the test diagnosis data of the subjects and suggests the most efficient approach to classify into 3 classes by data preprocessingand Hyperparameter optimization.
About the journal
JournalInternational Journal of Science and Research (IJSR)
PublisherInternational Journal of Science and Research (IJSR)
Open Access0