Classification of Dementia Detection Using Hybrid Neuro Multi-kernel SVM (NMKSVM)

Deep learning has played a vital role in the prediction of diseases in medical images. Early detection of disease will benefit people alive. However, it is a demanding task in neuroimaging. Convolutional neural network (CNN) works an essential role in predicting the early phases of dementia in the brain. There are seven phases in dementia. Early prognostication will aid to avert the gravity of the disease. Dementia is a chronic and continuing neurological issue. Dementia detection at the beginning can forestall the cerebrum (brain) harm to the patient. This research work recommends a hybrid neuro multi-kernel SVM (NMKSVM) approach. This able hybrid approach accomplishes the desired execution over conventional techniques such as SVM and CNN.