Accepted for/Published in: Journal of Medical Internet Research
Date Submitted: Aug 3, 2021
Date Accepted: Dec 16, 2021
Date Submitted to PubMed: Dec 17, 2021
Digital approaches to automated and machine learning assessments of hearing: a scoping review
ABSTRACT
Hearing loss affects one in five people worldwide and is estimated to affect one in four by 2050. Treatment relies on accurate diagnosis of hearing loss, but this first step is out of reach for more than 80% of those affected. Increasingly automated approaches are being developed for self-administered digital hearing assessment without professionals’ direct involvement. This scoping review provides an overview of automated approaches, based on 56 reports from 2012 until June 2021, adding to the 29 published prior to 2012. Twenty-seven automated approaches were identified with an increasing number reporting similar accuracy as manual hearing assessments. Machine learning approaches are more efficient and personal digital devices make assessments more affordable and accessible. Validity can be enhanced using digital technologies for quality surveillance including noise monitoring and detecting inconclusive results. Employed within identified limitations, automated assessments on digital devices can support task-shifting, self-care, virtual care, and clinical care pathways.
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