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Determining hearing threshold from Brain Stem Evoked Potentials - Optimising a neural network to improve classification performance

Alpsan, Dogan, Towsey, Michael W., Ozdamar, Ozcan, Tsoi, Ah Chung, & Ghista, Dhanjoo N. (1994) Determining hearing threshold from Brain Stem Evoked Potentials - Optimising a neural network to improve classification performance. IEEE Engineering in Medicine and Biology, 13(4), pp. 465-471.

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Abstract

Brain Stem Evoked Potentials (BAEPs) are considered the most objective measure currently available with which to determine the functional integrity of the peripheral auditory nervous system. Estimating hearing threshold from BAEP signals is a time consuming and laborious task, and therefore one which recommends itself to automation. In this paper we demonstrate that neural networks trained by back-propagation are an effective method to classify BAEPs. In order to achieve maxumum generalsiation, it was necesary to fine tune the learning parameters. Although this step can be time consuming, it has important clinical consequences.

Impact and interest:

9 citations in Scopus
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6 citations in Web of Science®

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ID Code: 7605
Item Type: Journal Article
Keywords: hearing, Brain Stem Evoked Potentials, neural networks
DOI: 10.1109/51.310986
ISSN: 0739-5175
Subjects: Australian and New Zealand Standard Research Classification > INFORMATION AND COMPUTING SCIENCES (080000) > ARTIFICIAL INTELLIGENCE AND IMAGE PROCESSING (080100) > Neural Evolutionary and Fuzzy Computation (080108)
Divisions: Past > QUT Faculties & Divisions > Faculty of Science and Technology
Copyright Owner: Copyright 1994 IEEE
Copyright Statement: Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.
Deposited On: 15 May 2007
Last Modified: 09 Jun 2010 22:40

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