Year: 2025
Type: article
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.
Author: Nasser Kehtarnavaz
Institution: The University of Texas at Dallas
Language: English
Subfield: Cognitive Neuroscience
Field: Neuroscience
Domain: Life Sciences
Open Access status: diamond
OpenAlex ID: W4411325870