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Reseach Article

Decision Support System for the Selection of an ITE or a BTE Hearing Aid

by Muhammad Naveed Anwar, Michael Philip Oakes
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 76 - Number 14
Year of Publication: 2013
Authors: Muhammad Naveed Anwar, Michael Philip Oakes
10.5120/13318-0936

Muhammad Naveed Anwar, Michael Philip Oakes . Decision Support System for the Selection of an ITE or a BTE Hearing Aid. International Journal of Computer Applications. 76, 14 ( August 2013), 37-42. DOI=10.5120/13318-0936

@article{ 10.5120/13318-0936,
author = { Muhammad Naveed Anwar, Michael Philip Oakes },
title = { Decision Support System for the Selection of an ITE or a BTE Hearing Aid },
journal = { International Journal of Computer Applications },
issue_date = { August 2013 },
volume = { 76 },
number = { 14 },
month = { August },
year = { 2013 },
issn = { 0975-8887 },
pages = { 37-42 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume76/number14/13318-0936/ },
doi = { 10.5120/13318-0936 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T21:45:56.046060+05:30
%A Muhammad Naveed Anwar
%A Michael Philip Oakes
%T Decision Support System for the Selection of an ITE or a BTE Hearing Aid
%J International Journal of Computer Applications
%@ 0975-8887
%V 76
%N 14
%P 37-42
%D 2013
%I Foundation of Computer Science (FCS), NY, USA
Abstract

The purpose of this research is to mine a large set of heterogeneous audiology data to create a decision support system (DSS) to choose between two hearing aid types (ITE and BTE aid). This research is based on the data analysis of audiology data using various statistical and data mining techniques. It uses the data of a large NHS (National Health Services, UK) facility. It uses 180,000 records (covering more than 23,000 different patients) from a hearing aid clinic. The developed system uses an unconventional method to predict hearing aid type for a patient and it can be used as a second opinion by audiologists for complex cases. After modifying the system to take account of the feedback from a professional audiologist, the success rates obtained were in the ranges 63 to 66 percent. In this research an automatic system was developed to choose between an ITE or a BTE hearing aid type with an explanation facility that can be used as a second opinion by audiologist in cases where the choice of an ITE or a BTE hearing aid is not clear cut. This analysis of audiology data and DSS will provide supplementary information for audiology experts and hearing aid dispensers. This type of system may also be of interest to manufacturers of hearing technologies in using as a ready means for their telephone customer services staff to check data, discovering data in audiology records will also be good for general awareness about the suitability of hearing aid type.

References
  1. Ananiadou, S. 2009. Text mining for biomedicine. In: Prince, V. , Roche, M. , eds. Information retrieval in biomedicine, natural language processing for knowledge integration. Medical information science reference, IGI Global, 1-9.
  2. Bakar, A. A. , Othman, Z. , Ismail, R. , Zakari, Z. 2009. Using the rough set theory for mining the level of hearing loss diagnosis knowledge. International conference on electrical engineering and informatics; Selangor, Malaysia, 7-11.
  3. Shalvi, D, DeClaris, N. 1998. An unsupervised neural network approach to medical data mining techniques. Neural Networks Proceedings, IEEE World Congress on Computational Intelligence, 171-176.
  4. Thompson, P. , Zhang, X. , Jiang, W. , Ras, Z. W. 2007. From mining tinnitus database to tinnitus decision support system, initial study. IEEE/WIC/ACM International conference on Intelligent Agent Technology, 203-206.
  5. Deafness Research UK Annual Review (dated: 6th August 2009) http://www. deafnessresearch. org. uk/ Deafness%20Research%20UK%20publishes%20Annual%20Review+5294. twl (accessed 6 July 2011)
  6. Bertoli, S. , Staehelin, K. , Zemp, E. , Schindler, C. , Bodmer, D. , et al. 2009. Survey on hearing aid use and satisfaction in Switzerland and their determinants. Int J Audiol,48:183-195.
  7. NHS: How can I get an NHS hearing aid? (dated: 9th February 2011) http://www. nhs. uk/chq/Pages/894. aspx ?CategoryID=68&SubCategoryID=157 (accessed 8 July 2011)
  8. Wong, L. L. N. , Hickson, L. , McPherson, B. 2009. Satisfaction with hearing aids: A consumer research perspective. Int J Audiol, 48:405-427.
  9. Tyler, R. , Coelho, C. , Tao, P. , Ji, H. , Gehringer, A. , et al. 2008. Identifying tinnitus subgroups with cluster analysis. Am J Audiol,17(2):76-184.
  10. Andersson, G. , McKenna, L. 1998. Tinnitus Masking and Depression. Int J Audiol, 37:174-182.
  11. Anwar, M. N. , Oakes, M. P. , Wermter, S. , Heinrich, S. Clustering Audiology Data. In 19th Annual Belgian-Dutch Conference on Machine Learning (BeneLearn 2010); Leuven, Belgium 2010. http://dtai. cs. kuleuven. be/events/Benelearn2010/submissions/benelearn2010_submission_7. pdf (accessed 24 June 2012)
  12. Anwar, M. N. , Oakes, M. P. , McGarry, K. 2011. Chi-squared, Yule's Q and Likelihood Ratios in Tabular Audiology Data. In: Ao, S. L. , and Gelman, L. , eds. Electrical Engineering and Applied Computing. Dordrecht: Springer Netherlands, 465-376.
  13. Witten, I. H. , Frank, E. , Hall, M. A. 2011. Data mining, practical machine learning tools and techniques. Third Edition. Morgan Kaufmann Publishers, 124-126,261-273.
  14. Han, J. , Kamber, M. , Pei, J. 2012. Data mining: concepts and techniques. Third Edition. Morgan Kaufmann Publishers, 350-351,393 -396.
  15. Manning, C. D. , Raghavan, P. , Schütze, H. 2008. Introduction to information retrieval. Cambridge University Press, 142-144.
  16. Manning, C. D. , Schütze, H. 1999. Foundations of statistical natural language processing. The MIT Press, 232-241.
  17. Cios, K. J. , Moore, G. W. 2002. Uniqueness of medical data mining. Artif Intell Med, 26:1-24.
Index Terms

Computer Science
Information Sciences

Keywords

ITE (in the ear) hearing aid BTE (behind the ear) hearing aid decision support system Naïve Bayesian analysis F-score.