Maximising the ability of stimulus-frequency otoacoustic emissions to predict hearing status and thresholds using machine-learning models

References

• Avan, P., P. Bonfils, D. Loth, P. Narcy, and J. Trotoux. 1991. “Quantitive Assessment of Human Cochlear Function by Evoked Otoacoustic Emissions.” Hearing Research 52 (1): 99–112. doi:10.1016/0378-5955(91)90191-B.
   PubMed Web of Science ®Google Scholar
• Bezdek, J. C., S. K. Chuah, and D. Leep. 1986. “Generalized k-Nearest Neighbor Rules.” Fuzzy Sets and Systems 18 (3): 237–256. doi:10.1016/0165-0114(86)90004-7.
   Web of Science ®Google Scholar
• Biswal, M., and S. K. Mishra. 2018. “Comparison of Time-Frequency Methods for Analyzing Stimulus Frequency Otoacoustic Emissions.” Journal of the Acoustical Society of America 143 (2): 626. doi:10.1121/1.5022783.
   PubMed Web of Science ®Google Scholar
• Boege, P., and T. Janssen. 2002. “Pure-Tone Threshold Estimation from Extrapolated Distortion Product Otoacoustic Emission I/O-Functions in Normal and Cochlear Hearing Loss Ears.” The Journal of the Acoustical Society of America 111 (4): 1810–1818. doi:10.1121/1.1460923.
   PubMed Web of Science ®Google Scholar
• Brass, D., and D. T. Kemp. 1993. “Suppression of Stimulus Frequency Otoacoustic Emissions.” The Journal of the Acoustical Society of America 93 (2): 920–939. doi:10.1121/1.405453.
   PubMed Web of Science ®Google Scholar
• Breiman, L. 2001. “Random Forests.” Machine Learning 45 (1): 5–32. doi:10.1023/A:1010933404324.
   Web of Science ®Google Scholar
• Brownell, W. E. 1990. “Outer Hair Cell Electromotility and Otoacoustic Emissions.” Ear and Hearing 11 (2): 82–92. doi:10.1097/00003446-199004000-00003
   PubMed Web of Science ®Google Scholar
• Burges, C. 1998. “A Tutorial on Support Vector Machines for Pattern Recognition.” Data Mining and Knowledge Discovery 2 (2): 121–167. doi:10.1023/A:1009715923555.
   Web of Science ®Google Scholar
• Chan, J. C., and D. Paelinckx. 2008. “Evaluation of Random Forest and Adaboost Tree-Based Ensemble Classification and Spectral Band Selection for Ecotope Mapping Using Airborne Hyperspectral Imagery.” Remote Sensing of Environment 112 (6): 2999–3011. doi:10.1016/j.rse.2008.02.011.
   Web of Science ®Google Scholar
• Daffertshofer, A., C. Lamoth, O. G. Meijer, and P. J. Beek. 2004. “PCA in Studying Coordination and Variability: A Tutorial.” Clinical Biomechanics (Bristol, Avon) 19 (4): 415–428. doi:10.1016/j.clinbiomech.2004.01.005.
   PubMed Web of Science ®Google Scholar
• Dorn, P. A., P. Piskorski, M. P. Gorga, S. T. Neely, and D. H. Keefe. 1999. “Predicting Audiometric Status from Distortion Product Otoacoustic Emissions Using Multivariate Analyses.” Ear and Hearing 20 (2): 149–163. doi:10.1097/00003446-199904000-00006
   PubMed Web of Science ®Google Scholar
• Ellison, J. C., and D. H. Keefe. 2005. “Audiometric Predictions Using Stimulus-Frequency Otoacoustic Emissions and Middle Ear Measurements.” Ear and Hearing 26 (5): 487–503. doi:10.1097/01.aud.0000179692.81851.3b.
   PubMed Web of Science ®Google Scholar
• Friedl, M. A., and C. E. Brodley. 1997. “Decision Tree Classification of Land Cover from Remotely Sensed Data.” Remote Sensing of Environment 61 (3): 399–409. doi:10.1016/S0034-4257(97)00049-7.
   Web of Science ®Google Scholar
• Go, N. A., G. C. Stamper, and T. A. Johnson. 2019. “Cochlear Mechanisms and Otoacoustic Emission Test Performance.” Ear and Hearing 40 (2): 401–417. doi:10.1097/AUD.0000000000000625
   PubMed Web of Science ®Google Scholar
• Gong, Q., Y. Wang, and M. Xian. 2014. “An Objective Assessment Method for Frequency Selectivity of the Human Auditory System.” Biomedical Engineering Online 13 (1): 171doi:10.1186/1475-925X-13-171.
   PubMedGoogle Scholar
• Gorga, M. P., S. T. Neely, B. Bergman, K. L. Beauchaine, J. R. Kaminski, J. Peters, L. Schulte, and W. Jesteadt. 1993a. “A Comparison of Transient-Evoked and Distortion Product Otoacoustic Emissions in Normal-Hearing and Hearing-Impaired Subjects.” The Journal of the Acoustical Society of America 94 (5): 2639–2648. doi:10.1121/1.407348.
   PubMed Web of Science ®Google Scholar
• Gorga, M. P., S. T. Neely, B. Bergman, K. L. Beauchaine, J. R. Kaminski, J. Peters, and W. Jesteadt. 1993b. “Otoacoustic Emissions from Normal-Hearing and Hearing-Impaired Subjects: Distortion Product Responses.” Journal of the Acoustical Society of America 93 (4 Pt 1): 2050–2060. doi:10.1121/1.406691.
   PubMed Web of Science ®Google Scholar
• Gorga, M. P., S. T. Neely, P. A. Dorn, and B. M. Hoover. 2003. “Further Efforts to Predict Pure-Tone Thresholds from Distortion Product Otoacoustic Emission Input/Output Functions.” Journal of the Acoustical Society of America 113 (6): 3275–3284. doi:10.1121/1.1570433.
   PubMed Web of Science ®Google Scholar
• Gorga, M. P., S. T. Neely, B. Ohlrich, B. Hoover, J. Redner, and J. Peters. 1997. “From Laboratory to Clinic: A Large Scale Study of Distortion Product Otoacoustic Emissions in Ears with Normal Hearing and Ears with Hearing Loss.” Ear and Hearing 18 (6): 440–455. doi:10.1097/00003446-199712000-00003
   PubMed Web of Science ®Google Scholar
• Huang, J., and C. X. Ling. 2005. “Using AUC and Accuracy in Evaluating Learning Algorithms.” IEEE Transactions on Knowledge and Data Engineering 17 (3): 299–310. doi:10.1109/TKDE.2005.50.
   Web of Science ®Google Scholar
• Hurley, R. M., and F. E. Musiek. 1994. “Effectiveness of Transient-Evoked Otoacoustic Emissions (TEOAEs) in Predicting Hearing Level.” Journal of the American Academy of Audiology 5 (3): 195.
   PubMedGoogle Scholar
• Hussain, D. M., M. P. Gorga, S. T. Neely, D. H. Keefe, and J. Peters. 1998. “Transient Evoked Otoacoustic Emissions in Patients with Normal Hearing and in Patients with Hearing Loss.” Ear and Hearing 19 (6): 434–449. doi:10.1097/00003446-199812000-00005
   PubMed Web of Science ®Google Scholar
• Johnson, T. A., and L. G. Baranowski. 2012. “The Influence of Common Stimulus Parameters on Distortion Product Otoacoustic Emission Fine Structure.” Ear and Hearing 33 (2): 239–249. doi:10.1097/AUD.0b013e3182321da4
   PubMed Web of Science ®Google Scholar
• Johnson, T. A., S. T. Neely, J. G. Kopun, D. M. Dierking, H. Tan, C. Converse, E. Kennedy, and M. P. Gorga. 2007. “Distortion Product Otoacoustic Emissions: Cochlear-Source Contributions and Clinical Test Performance.” Journal of the Acoustical Society of America 122 (6): 3539–3553. doi:10.1121/1.2799474.
   PubMed Web of Science ®Google Scholar
• Kalluri, R., and C. A. Shera. 2013. “Measuring Stimulus-Frequency Otoacoustic Emissions Using Swept Tones.” Journal of the Acoustical Society of America 134 (1): 356–368. doi:10.1121/1.4807505.
   PubMed Web of Science ®Google Scholar
• Kemp, D. T. 1978. “Stimulated Acoustic Emissions from within the Human Auditory System.” The Journal of the Acoustical Society of America 64 (5): 1386–1391. doi:10.1121/1.382104.
   PubMed Web of Science ®Google Scholar
• Kim, D. O., J. Paparello, M. D. Jung, J. Smurzynski, and X. Sun. 1996. “Distortion Product Otoacoustic Emission Test of Sensorineural Hearing Loss: Performance Regarding Sensitivity, Specificity and Receiver Operating Characteristics.” Acta Oto-Laryngologica 116 (1): 3–11. doi:10.3109/00016489609137705.
   PubMed Web of Science ®Google Scholar
• Lichtenstein, V., and D. R. Stapells. 1996. “Frequency-Specific Identification of Hearing Loss Using Transient-Evoked Otoacoustic Emissions to Clicks and Tones.” Hearing Research 98 (1-2): 125–136. doi:10.1016/0378-5955(96)00084-6.
   PubMed Web of Science ®Google Scholar
• Mertes, I. B., and S. S. Goodman. 2013. “Short-Latency Transient-Evoked Otoacoustic Emissions as Predictors of Hearing Status and Thresholds.” Journal of the Acoustical Society of America 134 (3): 2127–2135. doi:10.1121/1.4817831.
   PubMed Web of Science ®Google Scholar
• Pedregosa, F., G. Varoquaux, A. Gramfort, V. Michel, B. Thirion, O. Grisel, M. Blondel, et al. 2011. “Scikit-Learn: Machine Learning in Python.” Journal of Machine Learning Research 12: 2825–2830.
   Web of Science ®Google Scholar
• Prieve, B. A., M. P. Gorga, A. Schmidt, S. Neely, J. Peters, L. Schultes, and W. Jesteadt. 1993. “Analysis of Transient-Evoked Otoacoustic Emissions in Normal-Hearing and Hearing-Impaired Ears.” Journal of the Acoustical Society of America 93 (6): 3308–3319. doi:10.1121/1.405715.
   PubMed Web of Science ®Google Scholar
• Rumelhart, D. E., G. E. Hinton, and R. J. Williams. 1986. “Learning Representations by Back-Propagating.” Nature 323 (6088): 533–536. doi:10.1038/323533a0.
   Web of Science ®Google Scholar
• Shera, C. A., and C. Bergevin. 2012. “Obtaining Reliable Phase-Gradient Delays from Otoacoustic Emission Data.” Journal of the Acoustical Society of America 132 (2): 927–943. doi:10.1121/1.4730916.
   PubMed Web of Science ®Google Scholar
• Shera, C. A., and J. J. Guinan. 1999. “Evoked Otoacoustic Emissions Arise by Two Fundamentally Different Mechanisms: A Taxonomy for Mammalian OAEs.” Journal of the Acoustical Society of America 105 (2 Pt 1): 782–798. doi:10.1121/1.426948.
   PubMed Web of Science ®Google Scholar
• Sisto, R., S. Chelotti, L. Moriconi, S. Pellegrini, A. Citroni, V. Monechi, R. Gaeta, I. Pinto, N. Stacchini, and A. Moleti. 2007. “Otoacoustic Emission Sensitivity to Low Levels of Noise-Induced Hearing Loss.” The Journal of the Acoustical Society of America 122 (1): 387–401. doi:10.1121/1.2737668.
   PubMed Web of Science ®Google Scholar
• Stover, L., M. P. Gorga, S. T. Neely, and D. Montoya. 1996. “Toward Optimizing the Clinical Utility of Distortion Product Otoacoustic Emission Measurements.” The Journal of the Acoustical Society of America 100 (2 Pt 1): 956–967. doi:10.1121/1.416207.
   PubMed Web of Science ®Google Scholar
• Wada, H., K. Ohyama, T. Kobayashi, T. Koike, and S. Noguchi. 1995. “Effect of Middle Ear on Otoacoustic Emissions.” Audiology 34 (4): 161–176. doi:10.3109/00206099509071910.
   PubMedGoogle Scholar