Intelligent Clinical Decision Support System for Diagnosis of Epilepsy.

      Аннотация: Electroencephalography is the most useful and cost effective modality for the diagnosis of epilepsy. The detection of these abnormalities by the visual inspection of EEG signals is very complex and time-consuming process and it requires highly skilled doctors. In most of the cases, epilepsy is controlled by the proper medical treatment. For that purpose, the proper and early diagnosis of epilepsy is required. A Clinical Decision Support System (DSS) has been developed for the diagnosis of epilepsy using the Artificial Intelligence Techniques. Different Neural Network based classifiers like MLP, GFFNN, ENN and SVM have been designed and optimized for the diagnosis of epilepsy. In addition, various feature extraction techniques like statistical parameters, Principal Component Analysis, FFT and Discrete Wavelet transform are used for the feature extraction and dimensionality reduction.

Ключевые слова: Artificial Intelligence, artificial neural network, DSS, EEG SIGNALS, Principal Component Analysis, Support Vector Machine, Wavelets, Epilepsy Diagnosis, Multi Layer Perceptron, Generalized Feed forward Neural Network, Elman Network