TY - JOUR
T1 - Computational Audiology
T2 - New Approaches to Advance Hearing Health Care in the Digital Age
AU - Wasmann, Jan Willem A.
AU - Lanting, Cris P.
AU - Huinck, Wendy J.
AU - Mylanus, Emmanuel A.M.
AU - van der Laak, Jeroen W.M.
AU - Govaerts, Paul J.
AU - Swanepoel, De Wet
AU - Moore, David R.
AU - Barbour, Dennis L.
N1 - Funding Information:
D.R.M. and D.W.S. received support from NIH grant R21DC016241. D.R.M. receives support from the NIHR Manchester Biomedical Research Centre. The Radboudumc ENT department receives research funding from Cochlear, MED-EL, and Oticon Medical.
Publisher Copyright:
© 2021 Lippincott Williams and Wilkins. All rights reserved.
PY - 2021/11/1
Y1 - 2021/11/1
N2 - The global digital transformation enables computational audiology for advanced clinical applications that can reduce the global burden of hearing loss. In this article, we describe emerging hearing-related artificial intelligence applications and argue for their potential to improve access, precision, and efficiency of hearing health care services. Also, we raise awareness of risks that must be addressed to enable a safe digital transformation in audiology. We envision a future where computational audiology is implemented via interoperable systems using shared data and where health care providers adopt expanded roles within a network of distributed expertise. This effort should take place in a health care system where privacy, responsibility of each stakeholder, and patients' safety and autonomy are all guarded by design.
AB - The global digital transformation enables computational audiology for advanced clinical applications that can reduce the global burden of hearing loss. In this article, we describe emerging hearing-related artificial intelligence applications and argue for their potential to improve access, precision, and efficiency of hearing health care services. Also, we raise awareness of risks that must be addressed to enable a safe digital transformation in audiology. We envision a future where computational audiology is implemented via interoperable systems using shared data and where health care providers adopt expanded roles within a network of distributed expertise. This effort should take place in a health care system where privacy, responsibility of each stakeholder, and patients' safety and autonomy are all guarded by design.
KW - Artificial intelligence
KW - Big data
KW - Computational audiology
KW - Computational infrastructure
KW - Digital hearing health care
KW - Hearing loss
KW - Machine learning
UR - http://www.scopus.com/inward/record.url?scp=85103588121&partnerID=8YFLogxK
U2 - 10.1097/AUD.0000000000001041
DO - 10.1097/AUD.0000000000001041
M3 - Article
C2 - 33675587
AN - SCOPUS:85103588121
SN - 0196-0202
VL - 42
SP - 1499
EP - 1507
JO - Ear and hearing
JF - Ear and hearing
IS - 6
ER -