Abstract:The study includes three subgroups of Multiple Sclerosis, namely RRMS, SPMS and PPMS as well as healthy individuals. The purpose of this study is to diagnose Multiple Sclerosis subgroups through Magnetic Resonance Imaging and Expanded Status Disability Scale. MRI and EDSS data belong to 139 volunteers, 120 of whom are MS patients (76 RRMS, 38 SPMS, 6 PPMS patients) and the remaining are healthy people. All subjects are between the ages of 20 and 55. Disability levels of MS symptoms are determined using Expanded Disability Status Scale. We have focused on three regions in the brain: brain stem, periventricular corpus callosum, and upper cervical regions. EDSS scores and number of lesions in these three regions are considered as the parameters of the ANN algorithms to determine the subgroups of the disease. The empirical results are examined taking two aspects into consideration. One of them is MRI and the other is EDSS data. These two elements are applied onto the input of Artificial Neural Networks Algorithms that are Feed Forward Back Propagation, Learning Vector Quantization and Radial Basis Function. The significance of these variables for the diagnosis of MS subgroups has been revealed as a result of this study in which algorithm has been utilized.

The Wechsler Adult Intelligence Scale-Revised is a test designed and applied comprehensively for classifying the cognitive skills of adults. Different intellectual profiles on a sample population of 414 individuals, have been obtained to measure the relationship between the mental functioning or psychopathological disorder of the individuals based on the data through the Wechsler Adult Intelligence Scale-Revised test. The relevant data have been collected and considered as input neuron for Artificial Neural Networks and Support Vector Machine Radial Basis Function kernel Algorithms. Classification accuracy, time elapsed for training procedure and accuracy rate have been obtained through Multi Layer Perceptron. The training data is split as follows: 70% is the training data, 15% is the validation data and 15% is the test data. In addition, in Support Vector Machine, time elapsed and accuracy rate have been evaluated based on 5-fold cross validation method. As a result, we will show the importance of Working Memory profile (Numbering, Assembly Ability) of The Wechsler Adult Intelligence Scale-Revised test on adults for the analysis of psychopathological disorder.