A decision support system for the classification of event-related potentials

In this paper a decision support system (DSS) for the classification of patients on their collected event related potentials (ERPs) is proposed. The DSS consists of two levels: the feature extraction level and the classification level. The feature extraction level comprises the implementation of the...

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Veröffentlicht in:Neurel 2002 : 2002 6th Seminar on Neural Network Applications in Electrical Engineering proceedings, September 26-28, 2002 S. 159 - 164
Hauptverfasser: Vasios, C.E., Matsopoulos, G.K., Nikita, K.S., Uzunoglu, N., Papageorgiou, C.
Format: Tagungsbericht
Sprache:Englisch
Veröffentlicht: IEEE 2002
Schlagworte:
Brain modeling
Data mining
Decision support systems
Delay estimation
Drugs
Electroencephalography
Enterprise resource planning
Feature extraction
Multi-layer neural network
Neural networks
ISBN:0780375939, 9780780375932
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Abstract In this paper a decision support system (DSS) for the classification of patients on their collected event related potentials (ERPs) is proposed. The DSS consists of two levels: the feature extraction level and the classification level. The feature extraction level comprises the implementation of the multivariate autoregressive model in conjunction with a global optimization method, for the selection of optimum features from ERPs. The classification level is implemented with a single three-layer neural network, trained with the backpropagation algorithm and classifies the data into two classes: patients and control subjects. The DSS has been thoroughly tested to a number of patient data (OCD, FES, depressives and drug users), resulting successful classification up to 100%.
AbstractList In this paper a decision support system (DSS) for the classification of patients on their collected event related potentials (ERPs) is proposed. The DSS consists of two levels: the feature extraction level and the classification level. The feature extraction level comprises the implementation of the multivariate autoregressive model in conjunction with a global optimization method, for the selection of optimum features from ERPs. The classification level is implemented with a single three-layer neural network, trained with the backpropagation algorithm and classifies the data into two classes: patients and control subjects. The DSS has been thoroughly tested to a number of patient data (OCD, FES, depressives and drug users), resulting successful classification up to 100%.
Author Papageorgiou, C.
Nikita, K.S.
Uzunoglu, N.
Vasios, C.E.
Matsopoulos, G.K.
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Snippet In this paper a decision support system (DSS) for the classification of patients on their collected event related potentials (ERPs) is proposed. The DSS...
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StartPage 159
SubjectTerms Brain modeling
Data mining
Decision support systems
Delay estimation
Drugs
Electroencephalography
Enterprise resource planning
Feature extraction
Multi-layer neural network
Neural networks
Title A decision support system for the classification of event-related potentials
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