Hearing Aid Classification Based on Audiology Data

Panchev, Christo, Anwar, M N and Oakes, Michael (2013) Hearing Aid Classification Based on Audiology Data. In: International Conference on Artificial Neural Networks (ICANN),, 10 – 13 Sep 2013, Sofia, Bulgaria..

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Abstract

Presented is a comparative study of two machine learning models (MLP Neural Network and Bayesian Network) as part of a decision support system for prescribing ITE (in the ear) and BTE (behind the ear) aids for people with hearing difficulties. The models are developed/trained and evaluated on a large set of patient records from major NHS audiology centre in England. The two main questions which the models aim to address are: 1) What type of
hearing aid (ITE/BTE) should be prescribed to the patient? and 2) Which factors influence the choice of ITE as opposed to BTE hearing aids? The models developed here were evaluated against actual prescriptions given by the
doctors and showed relatively high classification rates with the MLP network achieving slightly better results.

Item Type: Conference or Workshop Item (Paper)
Subjects: Computing > Artificial Intelligence
Divisions: Faculty of Technology
Faculty of Technology > School of Computer Science
Depositing User: Glenda Young
Date Deposited: 03 Jul 2013 11:06
Last Modified: 18 Dec 2019 15:35
URI: http://sure.sunderland.ac.uk/id/eprint/3968

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