World report on hearing. World Health Organization, Geneva, CH, 2021.

J. D. Pearson et al. (1995), “Gender differences in a longitudinal study of age-associated hearing loss,” J Acoust Soc Am, 97(2), 1196–1205, https://doi.org/10.1121/1.412231.

Article  CAS  PubMed  Google Scholar 

K. J. Cruickshanks et al. (1998), “Prevalence of hearing loss in older adults in Beaver Dam, Wisconsin: The epidemiology of hearing loss study,” Am J Epidemiol, 148(9), 879–886, https://doi.org/10.1093/oxfordjournals.aje.a009713.

Article  CAS  PubMed  Google Scholar 

F.-S. Lee, L. J. Matthews, J. R. Dubno, and J. H. Mills (2005), “Longitudinal study of pure-tone thresholds in older persons,” Ear Hear, 26(1), 1–11, https://doi.org/10.1097/00003446-200502000-00001.

Article  PubMed  Google Scholar 

L. K. Dillard, M. O. Arunda, L. Lopez-Perez, R. X. Martinez, L. Jiménez, and S. Chadha (2022), “Prevalence and global estimates of unsafe listening practices in adolescents and young adults: A systematic review and meta-analysis,” BMJ Glob Health, 7(11), e010501, https://doi.org/10.1136/bmjgh-2022-010501.

Article  Google Scholar 

L. K. Dillard et al. (2023), “Associations of hearing loss and hearing aid use with cognition, health-related quality of life, and depressive symptoms,” J Aging Health, 35(7–8), 455–465, https://doi.org/10.1177/08982643221138162.

Article  PubMed  Google Scholar 

D. S. Dalton, K. J. Cruickshanks, B. E. K. Klein, R. Klein, T. L. Wiley, and D. M. Nondahl (2003), “The impact of hearing loss on quality of life in older adults,” Gerontologist, 43(5), 661–668, https://doi.org/10.1093/geront/43.5.661.

Article  PubMed  Google Scholar 

F. R. Lin, L. Ferrucci, E. J. Metter, Y. An, A. B. Zonderman, and S. M. Resnick (2011), “Hearing loss and cognition in the Baltimore longitudinal study of aging,” Neuropsychology, 25(6), 763–770, https://doi.org/10.1037/a0024238.

Article  PubMed  PubMed Central  Google Scholar 

C. R. Schubert et al. (2017), “Sensory impairments and cognitive function in middle-aged adults,” J Gerontol A Biol Sci Med Sci Ser A, 72(8), 1087–1090, https://doi.org/10.1093/gerona/glx067.

Article  Google Scholar 

Guidelines for manual pure-tone audiometry. American Speech-Language-Hearing Association, Rockville, MD, 2005. https://www.asha.org/policy/gl2005-00014/.

American national standard specifications for audiometers. American National Standards Institute (ANSI) S3.6-2018, New York, NY, 2018.

W. Hughson and H. Westlake (1944), “Manual for program outline for rehabilitation of aural casualties both military and civilian,” Trans of Am Acad of Ophthalmol Otolaryngol, 48, 1–15.

Google Scholar 

C. A. Mangham (1991), “Hearing threshold difference between ears and risk of acoustic tumor,” Otolaryngol Head Neck Surg, 105(6), 814–817, https://doi.org/10.1177/019459989110500607.

Article  CAS  PubMed  Google Scholar 

R. S. Schlauch and P. Nelson (2014), “Pure tone evaluation,” in Handbook of Clinical Audiology, 7th ed., J. Katz, M. Chasin, K. English, L. J. Hood, and K. L. Tillery, Eds., pp. 29–47.

R. Goldbrunner et al. (2019), “EANO guideline on the diagnosis and treatment of vestibular schwannoma,” Neuro Oncol, 22(1), 31–45, https://doi.org/10.1093/neuonc/noz153.

Article  PubMed Central  Google Scholar 

Guidelines for audiometric symbols. American Speech-Language-Hearing Association, Rockville, MD, 1990. https://pubmed.ncbi.nlm.nih.gov/1970250/.

R. H. Margolis and D. E. Morgan (2008), “Automated pure-tone audiometry: An analysis of capacity, need, and benefit,” Am J Audiol, 17(2), 109–113, https://doi.org/10.1044/1059-0889(2008/07-0047).

Article  PubMed  Google Scholar 

D. A. Vogel, P. A. McCarthy, G. W. Bratt, and C. Brewer (2007), “The clinical audiogram: Its history and current use,” Comm Dis Rev, 1(2), 81–94.

Google Scholar 

J. M. Krebs (2008), “Paper, paper everywhere? How to go paperless in your private practice,” The ASHA Leader. [Online]. Available: https://doi.org/10.1044/leader.FTR3.13122008.20

C. Murphy and I. J. Keogh (2023), “The evolution of the medical record from paper to digital: An ENT perspective,” J Laryngol Otol, 137(3), 246–248, https://doi.org/10.1017/s0022215122002018.

Article  CAS  PubMed  Google Scholar 

S. Das, A. Dey, A. Pal, and N. Roy (2015), “Applications of artificial intelligence in machine-learning: Review and prospect,” Int J Comput Appl, 115(9), 31–41, https://doi.org/10.5120/20182-2402.

Article  Google Scholar 

S. Li, C. Lu, L. Li, J. Duan, X. Fu, and H. Zhou (2021), “Interpreting audiograms with multi-stage neural networks,” Arxiv, 1–12, https://doi.org/10.48550/arxiv.2112.09357.

F. Charih and J. R. Green (2022), “Audiogram digitization tool for audiological reports,” IEEE Access, 10(1), 110761–110769, https://doi.org/10.1109/access.2022.3215972.

Article  Google Scholar 

K. He, X. Zhang, S. Ren, and J. Sun (2016), “Deep residual learning for image recognition,” in 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 770–778, https://doi.org/10.1109/cvpr.2016.90.

M. G. Crowson et al. (2020), “AutoAudio: Deep learning for automatic audiogram interpretation,” J Med Syst, 44(163), 1–7, https://doi.org/10.1007/s10916-020-01627-1.

Article  Google Scholar 

R. Girshick (2015), “Fast R-CNN,” in 2015 IEEE International Conference on Computer Vision (ICCV). 2015, 440–1448, https://doi.org/10.1109/iccv.2015.169.

G. 27. “YOLOv5 Version 7.0,” distributed by Ultralytics, https://doi.org/10.5281/zenodo.3908559.

The MathWorks, Inc. (2022). MATLAB version: 9.13.0 (R2022b). Available: https://www.mathworks.com.

P. Dollar, R. Appel, S. Belongie, and P. Perona (2014), “Fast feature pyramids for object detection,” IEEE Trans Pattern Anal Mach Intell, 36(8), 1532–1545, https://doi.org/10.1109/tpami.2014.2300479.

Article  PubMed  Google Scholar 

A. R. Robertson (1977), “The CIE 1976 color-difference formulae,” Color Res. Appl., 2(1), 7–11, https://doi.org/10.1002/j.1520-6378.1977.tb00104.x.

Article  Google Scholar 

J. Friedman, T. Hastie, and R. Tibshirani (2000), “Additive logistic regression: A statistical view of boosting,” Ann Statistics, 28(2), 337–407, https://doi.org/10.1214/aos/1016218223.

Article  Google Scholar 

P. Dollar, S. Belongie, and P. Perona (2010), “The fastest pedestrian detector in the west,” in Procedings of the British Machine Vision Conference 2010. 2010, 68.1-68.11. https://doi.org/10.5244/c.24.68.

P. Dollar, Piotr’s MATLAB Computer Vision Toolbox. Available: https://pdollar.github.io/toolbox/

The MathWorks, Inc. (2022). Computer Vision Toolbox version: 9.4 (R2022b). Available: https://www.mathworks.com

A. J. Newell and L. D. Griffin (2011), “Multiscale histogram of oriented gradient descriptors for robust character recognition,” in 2011 International Conference on Document Analysis and Recognition. 2011, 1085–1089. https://doi.org/10.1109/icdar.2011.219.

The MathWorks, Inc. (2022). Statistics and Machine Learning Toolbox version: 11.4 (R2022b). Available: https://www.mathworks.com

R. Padilla, S. L. Netto, and E. A. B. D. Silva (2020), “A survey on performance metrics for object-detection algorithms,” in 2020 International Conference on Systems, Signals and Image Processing (IWSSIP), 2020, 237–242. https://doi.org/10.1109/iwssip48289.2020.9145130.

D. Ghosh, T. Dube, and A. P. Shivaprasad (2010), “Script recognition–a review,” IEEE Trans Pattern Anal Mach Intell, 32(12), 2142–2161, https://doi.org/10.1109/tpami.2010.30.

Article  PubMed  Google Scholar