Intelligent Clinical Decision Support System for Diagnosis of Epilepsy - Dudul, Sanjay;Kharat, Pravin
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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…mehr

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Produktbeschreibung
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.
Autorenporträt
Sanjay Dudul(B.E.,M.E.& Ph.D.)is a Professor and HOD of Applied Electronics at SGB Amravati University.He published 102 articles in refereed International Journals.He has filed 6 Patents. So far 13 students are awarded Ph.D. under his guidance. He has 28 yrs teaching (UG,PG) & 18 yrs research experience(Image Processing & Artificial Intelligence).