Intelligent Clinical Decision Support System for Diagnosis of Epilepsy

Sanjay Dudul (u. a.)

ISBN 10: 3330019646 / ISBN 13: 9783330019645

Edité par LAP Lambert Academic Publishing, 2017

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. N° de réf. du vendeur 108388804

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.

Présentation de l'éditeur: 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.

Détails bibliographiques

Titre : Intelligent Clinical Decision Support System...
Éditeur : LAP Lambert Academic Publishing
Date d'édition : 2017
Reliure : Taschenbuch
Etat : Neu