DocumentCode :
1915496
Title :
Multi-neural networks approaches for biomedical applications: classification of brainstem auditory evoked potentials
Author :
Dujardin, Anne-Sophie ; Amarger, Véronique ; Madani, Kurosh
Author_Institution :
SENART Inst. of Technol., Paris XII Univ., Lieusaint, France
Volume :
5
fYear :
1999
fDate :
1999
Firstpage :
3609
Abstract :
Auditory evoked potentials (AEPs) are electrical response caused by the brief stimulation of the auditory sensing system. AEP based techniques are important tools to diagnosis many of auditory pathologies. Especially to suspect the presence of auditory tumors called `acoustic neuromas´. We investigate the design of a neural based biomedical diagnosis aide tool. We use three models of artificial neural networks: learning vector quantization, radial basis function and backpropagation ones. In our approach these three neural networks are used to achieve the classification in two multi-neural network configurations. A case study and experimental results are reported and discussed
Keywords :
auditory evoked potentials; backpropagation; medical computing; neurophysiology; pattern classification; radial basis function networks; RBF neural networks; auditory evoked potentials; auditory sensing system; backpropagation neural net; brainstem; learning vector quantization; pattern classification; Acoustic noise; Artificial neural networks; Backpropagation; Biological neural networks; Circuit testing; Electric potential; Electronic mail; Image databases; Pathology; Vector quantization;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Neural Networks, 1999. IJCNN '99. International Joint Conference on
Conference_Location :
Washington, DC
ISSN :
1098-7576
Print_ISBN :
0-7803-5529-6
Type :
conf
DOI :
10.1109/IJCNN.1999.836253
Filename :
836253
Link To Document :
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