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