CFP last date
20 May 2024
Call for Paper
June Edition
IJCA solicits high quality original research papers for the upcoming June edition of the journal. The last date of research paper submission is 20 May 2024

Submit your paper
Know more
The week's pick
Responsive image
Enhancing Privacy Preservation: Multi-Attribute Protection with P-Sensitive K-Anonymity

Twinkle Patel Kiran Amin
Random Articles
Reseach Article

Identifying relationship between Hearing loss Symptoms and Pure-tone Audiometry Thresholds with FP-Growth Algorithm

by Nasir G. Noma, Mohd Khanapi Abd Ghani, Mohamad Khir Abdullah
journal cover thumbnail

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 65 - Number 21
Year of Publication: 2013
Authors: Nasir G. Noma, Mohd Khanapi Abd Ghani, Mohamad Khir Abdullah
10.5120/11209-6352

Nasir G. Noma, Mohd Khanapi Abd Ghani, Mohamad Khir Abdullah . Identifying relationship between Hearing loss Symptoms and Pure-tone Audiometry Thresholds with FP-Growth Algorithm. International Journal of Computer Applications. 65, 21 ( March 2013), 24-29. DOI=10.5120/11209-6352

@article{ 10.5120/11209-6352,
author = { Nasir G. Noma, Mohd Khanapi Abd Ghani, Mohamad Khir Abdullah },
title = { Identifying relationship between Hearing loss Symptoms and Pure-tone Audiometry Thresholds with FP-Growth Algorithm },
journal = { International Journal of Computer Applications },
issue_date = { March 2013 },
volume = { 65 },
number = { 21 },
month = { March },
year = { 2013 },
issn = { 0975-8887 },
pages = { 24-29 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume65/number21/11209-6352/ },
doi = { 10.5120/11209-6352 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T21:19:27.395464+05:30
%A Nasir G. Noma
%A Mohd Khanapi Abd Ghani
%A Mohamad Khir Abdullah
%T Identifying relationship between Hearing loss Symptoms and Pure-tone Audiometry Thresholds with FP-Growth Algorithm
%J International Journal of Computer Applications
%@ 0975-8887
%V 65
%N 21
%P 24-29
%D 2013
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Considerable numbers of studies have related audiometry hearing threshold values with various diseases and conditions that cause hearing loss. The purpose of this study was to find the relationship that exists between pure-tone audiometry threshold values and hearing loss symptoms in a medical datasets of 339 hearing loss patients using association rule mining algorithm. FP-Growth (Frequent Pattern) algorithm is employed for this purpose to generate itemsets given 0. 2 (20%) as the support threshold value and 0. 7 (70%) as the confidence value for association rule generation. Interesting relationships were discovered and the results were compared to earlier findings using the same method on a sample datasets of 50 hearing loss patients with 0. 1 as the minimum support and 0. 7 confidence thresholdsfor the association rule mining. There is similarity in the correlation that exists between symptoms and the pure-tone hearing thresholds from the initial study results and the correlation in the current study results. The experimental result with 339 patients medical datasets extends previously published findings on 50 patients' medical datasets and the sets of symptoms that appear together is consistent with current knowledge of those symptoms occurring together as evidenced clinically.

References
  1. C. Halpin and S. D. Rauch, 'Clinical implications of a damaged cochlea: pure tone thresholds vs information-carrying capacity', Otolaryngol Head Neck Surg, vol. 140, no. 4, pp. 473–476, Apr. 2009.
  2. J. H. Hwang, H. C. Ho, C. J. Hsu, W. S. Yang, and T. C. Liu, 'Diagnostic value of combining bilateral electrocochleography results for unilateral Ménière's disease', Audiol. Neurootol. , vol. 13, no. 6, pp. 365–369, 2008.
  3. Y. Agrawal, E. A. Platz, and J. K. Niparko, 'Risk factors for hearing loss in US adults: data from the National Health and Nutrition Examination Survey, 1999 to 2002', Otol. Neurotol. , vol. 30, no. 2, pp. 139–145, Feb. 2009.
  4. T. L. Wiley, R. Chappell, L. Carmichael, D. M. Nondahl, and K. J. Cruickshanks, 'Changes in hearing thresholds over 10 years in older adults', J Am Acad Audiol, vol. 19, no. 4, pp. 281–292; quiz 371, Apr. 2008.
  5. L. J. Brant and J. L. Fozard, 'Age changes in pure-tone hearing thresholds in a longitudinal study of normal human aging', J. Acoust. Soc. Am. , vol. 88, no. 2, pp. 813–820, Aug. 1990.
  6. H. O. Ahmed, J. H. Dennis, O. Badran, M. Ismail, S. G. Ballal, A. Ashoor, and D. Jerwood, 'High-frequency (10-18 kHz) hearing thresholds: reliability, and effects of age and occupational noise exposure', Occup Med (Lond), vol. 51, no. 4, pp. 245–258, Jun. 2001.
  7. G. A. Gates, P. Schmid, S. G. Kujawa, B. Nam, and R. D'Agostino, 'Longitudinal threshold changes in older men with audiometric notches', Hear. Res. , vol. 141, no. 1–2, pp. 220–228, Mar. 2000.
  8. S. Kim, E. J. Lim, H. S. Kim, J. H. Park, S. S. Jarng, and S. H. Lee, 'Sex Differences in a Cross Sectional Study of Age-related Hearing Loss in Korean', Clin Exp Otorhinolaryngol, vol. 3, no. 1, pp. 27–31, Mar. 2010.
  9. R. Jönsson, U. Rosenhall, I. Gause-Nilsson, and B. Steen, 'Auditory function in 70- and 75-year-olds of four age cohorts. A cross-sectional and time-lag study of presbyacusis', Scand Audiol, vol. 27, no. 2, pp. 81–93, 1998.
  10. F. -S. Lee, L. J. Matthews, J. R. Dubno, and J. H. Mills, 'Longitudinal study of pure-tone thresholds in older persons', Ear Hear, vol. 26, no. 1, pp. 1–11, Feb. 2005.
  11. C. Blanchet, C. Pommie, M. Mondain, C. Berr, D. Hillaire, and J. -L. Puel, 'Pure-tone threshold description of an elderly French screened population', Otol. Neurotol. , vol. 29, no. 4, pp. 432–440, Jun. 2008.
  12. N. Vaughan, K. James, D. McDermott, S. Griest, and S. Fausti, 'A 5-year prospective study of diabetes and hearing loss in a veteran population', Otol. Neurotol. , vol. 27, no. 1, pp. 37–43, Jan. 2006.
  13. A. -M. R. de Heer, P. L. M. Huygen, R. W. J. Collin, H. Kremer, and C. W. R. J. Cremers, 'Mild and variable audiometric and vestibular features in a third DFNA15 family with a novel mutation in POU4F3', Ann. Otol. Rhinol. Laryngol. , vol. 118, no. 4, pp. 313–320, Apr. 2009.
  14. M. N. Anwar and M. P. Oakes, 'Data mining of audiology patient records: factors influencing the choice of hearing aid type', in Proceedings of the ACM fifth international workshop on Data and text mining in biomedical informatics, New York, NY, USA, 2011, pp. 11–18.
  15. C. -Y. Lee, J. -H. Hwang, S. -J. Hou, and T. -C. Liu, 'Using cluster analysis to classify audiogram shapes', Int J Audiol, vol. 49, no. 9, pp. 628–633, Sep. 2010.
  16. M. Moein, M. Davarpanah, M. A. Montazeri, and M. Ataei, 'Classifying ear disorders using support vector machines', in 2010 Second International Conference on Computational Intelligence and Natural Computing Proceedings (CINC), Sept. , vol. 1, pp. 321–324.
  17. K. Varpa, K. Iltanen, and M. Juhola, 'Machine learning method for knowledge discovery experimented with otoneurological data', Comput Methods Programs Biomed, vol. 91, no. 2, pp. 154–164, Aug. 2008.
  18. P. -N. Tan, M. Steinbach, and V. Kumar, Introduction to Data Mining, 1st ed. Addison-Wesley, 2005.
  19. C. Sammut and G. I. Webb, Eds. , Encyclopedia of Machine Learning, 2010th ed. Springer, 2011.
  20. L. Ciletti and G. A. Flamme, 'Prevalence of hearing impairment by gender and audiometric configuration: results from the National Health and Nutrition Examination Survey (1999-2004) and the Keokuk County Rural Health Study (1994-1998)', J Am Acad Audiol, vol. 19, no. 9, pp. 672–685, Oct. 2008.
  21. K. C. P. Yuen and B. McPherson, 'Audiometric configurations of hearing impaired children in Hong Kong: implications for amplification', Disabil Rehabil, vol. 24, no. 17, pp. 904–913, Nov. 2002.
  22. K. C. P. Yuen and B. McPherson, 'Audiometric configurations of hearing impaired children in Hong Kong: implications for amplification', Disabil Rehabil, vol. 24, no. 17, pp. 904–913, Nov. 2002.
  23. N. Wickramasinghe, R. K. Bali, and B. Lehaney, Healthcare Knowledge Management Primer. Taylor & Francis, 2009.
  24. U. Fayyad, G. Piatetsky-shapiro, and P. Smyth, 'From Data Mining to Knowledge Discovery in Databases', AI Magazine, vol. 17, pp. 37–54, 1996.
  25. P. Cabena, Hadjnian, Stadler, Verhees, and Zanasi, Discovering Data Mining: From Concept to Implementation. Prentice Hall, 1997.
  26. P. Harrington, Machine Learning in Action. Manning Publications, 2012.
  27. Z. He, S. Deng, and X. Xu, 'An FP-Tree Based Approach for Mining All Strongly Correlated Item Pairs', in Computational Intelligence and Security, Y. Hao, J. Liu, Y. Wang, Y. Cheung, H. Yin, L. Jiao, J. Ma, and Y. -C. Jiao, Eds. Springer Berlin Heidelberg, 2005, pp. 735–740.
  28. P. Rajendran and M. Madheswaran, 'Hybrid Medical Image Classification Using Association Rule Mining with Decision Tree Algorithm', arXiv:1001. 3503, Jan. 2010.
  29. J. Han, J. Pei, Y. Yin, and R. Mao, 'Mining Frequent Patterns without Candidate Generation: A Frequent-Pattern Tree Approach', Data Min. Knowl. Discov. , vol. 8, no. 1, pp. 53–87, Jan. 2004.
  30. I. H. Witten, E. Frank, and M. A. Hall, Data Mining: Practical Machine Learning Tools and Techniques, Third Edition, 3rd ed. Morgan Kaufmann, 2011.
  31. V. L. Simoens and S. Hébert, 'Cortisol suppression and hearing thresholds in tinnitus after low-dose dexamethasone challenge', BMC Ear, Nose and Throat Disorders, vol. 12, no. 1, p. 4, Mar. 2012.
  32. M. K. A. Ghani, N. G. Noma, M. K. Abdullahi, N. Yahya, 'DiscoveringPattern in Medical Audiology Data with FP-GrowthAlgorithm', 2012 IEEE-EMBS International ConferenceonBiomedicalEngineering and Sciences, Dec. 2012.
Index Terms

Computer Science
Information Sciences

Keywords

Threshold Pure-tone FP-Growth sensorineural tinnitus vertigo

Powered by PhDFocusTM