Clinical Diagnosis of Alzheimer’s Disease Employing Support Vector Machine

With the progress in the field of medicine, no doubt the human life span has been increasing; eventually age-related diseases are also increasing. Dementia is one such disease associated with neurodegeneration. Alzheimer’s Disease is one of the types of Dementia. This study focuses on classifying the subjects using a Support Vector Machine.466 participants were tested using neuropsychological exams. The recorded readings are compared to the 10/66 Research group's suggested cut-off. The data set is preprocessed and classified using the SVM classifier and LibSVM using the Weka tool. The model is evaluated using Cross-validation and the Holdout method for both classifiers and the results are compared. SVM classifier gives an accuracy of 99.57% with 10-fold cross-validation. The results show SVM classifier gives better results both in cross-validation and holdout method in comparison with LibSVM. This study facilitates early intervention which in turn slows down the progression of the disease and enables the demented to have a quality life for the rest of the tenure.