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.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Ananiadou, S.: Text mining for biomedicine. In: Prince, V., Roche, M. (eds.) Information Retrieval in Biomedicine, Natural Language Processing for Knowledge Integration, Medical Information Science Reference, pp. 1–9. IGI Global, Prince (2009)
Bakar, A.A., Othman, Z., Ismail, R., Zakari, Z.: Using the rough set theory for mining the level of hearing loss diagnosis knowledge. In: International Conference on Electrical Engineering and Informatics, Selangor, Malaysia, pp. 7–11 (August 2009)
Shalvi, D., DeClaris, N.: An unsupervised neural network approach to medical data mining techniques. In: Proceedings of IEEE World Congress on Computational Inetelligence Neural Networks, pp. 171–176 (1998)
Thompson, P., Zhang, X., Jiang, W., Ras, Z.W.: From mining tinnitus database to tinnitus decision support system, initial study. In: IEEE/WIC/ACM International Conference on Intelligent Agent Technology, pp. 203–206 (2007)
Hagan, M.T., Menhaj, M.: Training feed-forward networks with the Marquardt algorithm. IEEE Transactions on Neural Networks 5(6), 989–993 (1999)
Anwar, M.N., Oakes, M.P.: Data Mining of Audiology Patient Records: Factors Influencing the Choice of Hearing Aid Type. Journal of BMC Medical Informatics & Decision Making 12(suppl. 1), S6 (2012)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2013 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Panchev, C., Anwar, M.N., Oakes, M. (2013). Hearing Aid Classification Based on Audiology Data. In: Mladenov, V., Koprinkova-Hristova, P., Palm, G., Villa, A.E.P., Appollini, B., Kasabov, N. (eds) Artificial Neural Networks and Machine Learning – ICANN 2013. ICANN 2013. Lecture Notes in Computer Science, vol 8131. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-40728-4_47
Download citation
DOI: https://doi.org/10.1007/978-3-642-40728-4_47
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-40727-7
Online ISBN: 978-3-642-40728-4
eBook Packages: Computer ScienceComputer Science (R0)