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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 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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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.
Biografía del autor
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
Verlag:
LAP Lambert Academic Publishing Feb 2017, 2017
ISBN 10: 3330019646
ISBN 13: 9783330019645
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Taschenbuch. Zustand: 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. Bestandsnummer des Verkäufers 9783330019645
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Intelligent Clinical Decision Support System for Diagnosis of Epilepsy
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ISBN 10: 3330019646
ISBN 13: 9783330019645
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Intelligent Clinical Decision Support System for Diagnosis of Epilepsy
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LAP LAMBERT Academic Publishing, 2017
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ISBN 13: 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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Intelligent Clinical Decision Support System for Diagnosis of Epilepsy
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ISBN 10: 3330019646
ISBN 13: 9783330019645
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Zustand: 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. Bestandsnummer des Verkäufers 159137360
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Intelligent Clinical Decision Support System for Diagnosis of Epilepsy
Verlag:
LAP Lambert Academic Publishing Feb 2017, 2017
ISBN 10: 3330019646
ISBN 13: 9783330019645
Neu
Taschenbuch
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Taschenbuch. Zustand: 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. Bestandsnummer des Verkäufers 9783330019645
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Intelligent Clinical Decision Support System for Diagnosis of Epilepsy
Verlag:
LAP Lambert Academic Publishing, 2017
ISBN 10: 3330019646
ISBN 13: 9783330019645
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Taschenbuch. Zustand: 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. Bestandsnummer des Verkäufers 9783330019645
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Intelligent Clinical Decision Support System for Diagnosis of Epilepsy
Verlag:
LAP LAMBERT Academic Publishing, 2017
ISBN 10: 3330019646
ISBN 13: 9783330019645
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Paperback. Zustand: Brand New. 140 pages. 8.66x5.91x0.32 inches. In Stock. Bestandsnummer des Verkäufers 3330019646
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