Main Article Content
Abstract
Emergence of neurodegenerative disorders with population aging is a major concern nowadays. Correct and timely diagnosis of these kinds of disorders is a major challenge faced by doctors and neurologists. This paper determines how different computer aided techniques and their applications have been utilized to develop expert systems for the diagnosis of neurodegenerative disorders (ND). It presents the consolidated outlook of research progress in the field of ND disorders through a literature survey from 2005 to 2019.This paper extends its discussion with the feature extraction methods along with the classification techniques primarily used for the construction of intelligent systems. It also identifies the research progress using the expertise of intelligent techniques for world’s top two neurodegenerative disorders: Alzheimer’s and Parkinson’s. The study identifies that principal component analysis (PCA) as a most widely used feature extraction method for representing the features in lower dimension. Support Vector Machines (SVM) with and without kernel functions are also showing their utility as a major classifier for most of the (Computer aided diagnosis) CAD systems. The survey is also identifying the usage of various kinds of datasets over the years for obtaining best results.