Synopsis
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.
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About the Author
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).
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Intelligent Clinical Decision Support System for Diagnosis of Epilepsy
Published by
LAP Lambert Academic Publishing Feb 2017, 2017
ISBN 10: 3330019646
ISBN 13: 9783330019645
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Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -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. 140 pp. Englisch. Seller Inventory # 9783330019645
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Intelligent Clinical Decision Support System for Diagnosis of Epilepsy
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Intelligent Clinical Decision Support System for Diagnosis of Epilepsy
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Intelligent Clinical Decision Support System for Diagnosis of Epilepsy
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Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Dudul SanjaySanjay 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. Seller Inventory # 159137360
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Intelligent Clinical Decision Support System for Diagnosis of Epilepsy
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Intelligent Clinical Decision Support System for Diagnosis of Epilepsy
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Intelligent Clinical Decision Support System for Diagnosis of Epilepsy
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Taschenbuch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -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.Books on Demand GmbH, Überseering 33, 22297 Hamburg 140 pp. Englisch. Seller Inventory # 9783330019645
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Intelligent Clinical Decision Support System for Diagnosis of Epilepsy
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LAP Lambert Academic Publishing, 2017
ISBN 10: 3330019646
ISBN 13: 9783330019645
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Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - 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. Seller Inventory # 9783330019645
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Intelligent Clinical Decision Support System for Diagnosis of Epilepsy
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Taschenbuch. Condition: Neu. Intelligent Clinical Decision Support System for Diagnosis of Epilepsy | Sanjay Dudul (u. a.) | Taschenbuch | 140 S. | Englisch | 2017 | LAP Lambert Academic Publishing | EAN 9783330019645 | Verantwortliche Person für die EU: BoD - Books on Demand, In de Tarpen 42, 22848 Norderstedt, info[at]bod[dot]de | Anbieter: preigu. Seller Inventory # 108388804