References:
1. Jones L, Golan D, Hanna S, Ramachandran M. Artificial intelligence,
machine learning and the evolution of healthcare: A bright future or
cause for concern? Bone & joint research. 2018;7(3):223-5.
2. Sayburn A. Will the machines take over surgery? The Bulletin of the
Royal College of Surgeons of England. 2017;99(3):88-90.
3. Balatsouras D, Koukoutsis G, Fassolis A, Moukos A, Apris A. Benign
paroxysmal positional vertigo in the elderly: current insights. Clinical
interventions in aging. 2018;13:2251.
4. Lim E-C, Park JH, Jeon HJ, Kim H-J, Lee H-J, Song C-G, et al.
Developing a Diagnostic Decision Support System for Benign Paroxysmal
Positional Vertigo Using a Deep-Learning Model. Journal of clinical
medicine. 2019;8(5):633.
5. Acharya V, Haywood M, Kokkinos N, Raithatha A, Francis S, Sharma R.
Does focused and dedicated teaching improve the confidence of GP
trainees to diagnose and manage common acute ENT pathologies in primary
care? Advances in medical education and practice. 2018;9:335.
6. RCS. RCS: Future of Surgery 2018 [Available from:
https://futureofsurgery.rcseng.ac.uk/?_ga=2.134153868.344240087.1578048159-1041599817.1578048159.
7. Haan M, Ongena YP, Hommes S, Kwee TC, Yakar D. A Qualitative Study to
Understand Patient Perspective on the Use of Artificial Intelligence in
Radiology. Journal of the American College of Radiology: JACR. 2019.
8. Bing D, Ying J, Miao J, Lan L, Wang D, Zhao L, et al. Predicting the
hearing outcome in sudden sensorineural hearing loss via machine
learning models. Clinical Otolaryngology. 2018;43(3):868-74.
9. Olze H, Uecker FC, Haeussler SM, Knopke S, Szczepek AJ, Graebel S.
Hearing Implants in the Era of Digitization. Laryngo-rhino-otologie.
2019;98(S 01):S82-S128.
10. Myburgh HC, van Zijl WH, Swanepoel D, Hellström S, Laurent C. Otitis
Media Diagnosis for Developing Countries Using Tympanic Membrane
Image-Analysis. EBioMedicine. 2016;5:156-60.
11. news EaA. The hearScope 2017 [Available from:
https://www.entandaudiologynews.com/development/spotlight-on-innovation/post/the-hearscope-in-conversation-with-de-wet-swanepoel.
12. Bur AM, Shew M, New J. Artificial Intelligence for the
Otolaryngologist: A State of the Art Review. Otolaryngology–Head and
Neck Surgery. 2019;160(4):603-11.
13. Fei B, Lu G, Wang X, Zhang H, Little JV, Patel MR, et al. Label-free
reflectance hyperspectral imaging for tumor margin assessment: a pilot
study on surgical specimens of cancer patients. Journal of biomedical
optics. 2017;22(8):086009.
14. Arambula AM, Bur AM. Ethical Considerations in the Advent of
Artificial Intelligence in Otolaryngology. Otolaryngology–Head and Neck
Surgery. 2020;162(1):38-9.