Impact of Machine Learning on the Future of Hearing Aid Fitting

The standard approach to hearing aid fitting currently relies on average-based prescriptive amplification, which lacks a systematic integration of individual hearing preferences. However, machine learning, an emerging tool across various sectors of healthcare, offers a promising approach to incorporate personal hearing preferences into routine fittings. This short communication outlines the prevailing practices in hearing aid fitting and how machine learning can impact hearing outcomes in audio environments that matter most to an individual hearing aid user.

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Publication Details

Journal
Biomedical Journal of Scientific & Technical Research
Published
2025-05-22
DOI
https://doi.org/10.26717/bjstr.2025.62.009683
Primary Topic
Noise Effects and Management
Type
article
Field-Weighted Citation Impact
0.00
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article

Impact of Machine Learning on the Future of Hearing Aid Fitting

Nasser Kehtarnavaz
Biomedical Journal of Scientific & Technical Research
Noise Effects and Management
article

Impact of Machine Learning on the Future of Hearing Aid Fitting

Nasser Kehtarnavaz
article en

Abstract

The standard approach to hearing aid fitting currently relies on average-based prescriptive amplification, which lacks a systematic integration of individual hearing preferences. However, machine learning, an emerging tool across various sectors of healthcare, offers a promising approach to incorporate personal hearing preferences into routine fittings. This short communication outlines the prevailing practices in hearing aid fitting and how machine learning can impact hearing outcomes in audio environments that matter most to an individual hearing aid user.

Biomedical Journal of Scientific & Technical ResearchVol. 62(1)
The University of Texas at Dallas (US), University of North Texas at Dallas (US)
Openalex Percentile: Top 82%
Noise Effects and Management
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