Artificial Intelligence and Telehealth as Diagnostic Approach to Middle Ear Disease- Advances in Otology
DOI:
https://doi.org/10.51985/JBUMDC2023168Abstract
As with other subspecialities, remote otoscopy commonly
regarded as telehealth is being studied as a new approach
for diagnosis of middle ear diseases
References
Ezzibdeh R, Munjal T, Ahmad I, Valdez TA. Artificial
intelligence and tele-otoscopy: A window into the future of
paediatric otology. Int J Pediatr Otorhinolaryngol. 2022
Sep;160:111229. DOI: 10.1016/j.ijporl.2022.111229
Pedersen, J. E. N. (2020). Digital otoscopy with AI diagnostic
support: making diagnosis of ear disease more accessible.
ENT & Audiology News.
Sandström J, Myburgh H, Laurent C, Swanepoel DW,
Lundberg T. A Machine Learning Approach to Screen for
Otitis Media Using Digital Otoscope Images Labelled by an
Expert Panel. Diagnostics. 2022; 12(6):1318 DOI:
https://doi.org/10.3390/diagnostics12061318
Chen YC, Chu YC, Huang CY, Lee YT, Lee WY, Hsu CY,
Yang AC, Liao WH, Cheng YF. Smartphone-based artificial
intelligence using a transfer learning algorithm for the detection
and diagnosis of middle ear diseases: A retrospective deep
learning study. EClinicalMedicine. 2022 Sep 1;51:101543.
DOI: https://doi.org/10.1016/j.eclinm.2022.101543
Habib, A-R, Kajbafzadeh, M, Hasan, Z, et al. Artificial
intelligence to classify ear disease from otoscopy: A systematic
review and meta-analysis. Clin Otolaryngol. 2022; 47: 401–
DOI: DOI: 10.1111/coa.13925
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Copyright (c) 2023 Soubia Akhtar, Yumna Afzal
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