• 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