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. 2024 Nov 6;24(22):7126.
doi: 10.3390/s24227126.

Artificial Intelligence in Audiology: A Scoping Review of Current Applications and Future Directions

Andrea Frosolini  1 , Leonardo Franz  2 , Valeria Caragli  3 , Elisabetta Genovese  3   4 , Cosimo de Filippis  2 , Gino Marioni  2
Affiliations

Artificial Intelligence in Audiology: A Scoping Review of Current Applications and Future Directions

Andrea Frosolini et al. Sensors (Basel). .

Abstract

The integration of artificial intelligence (AI) into medical disciplines is rapidly transforming healthcare delivery, with audiology being no exception. By synthesizing the existing literature, this review seeks to inform clinicians, researchers, and policymakers about the potential and challenges of integrating AI into audiological practice. The PubMed, Cochrane, and Google Scholar databases were searched for articles published in English from 1990 to 2024 with the following query: "(audiology) AND ("artificial intelligence" OR "machine learning" OR "deep learning")". The PRISMA extension for scoping reviews (PRISMA-ScR) was followed. The database research yielded 1359 results, and the selection process led to the inclusion of 104 manuscripts. The integration of AI in audiology has evolved significantly over the succeeding decades, with 87.5% of manuscripts published in the last 4 years. Most types of AI were consistently used for specific purposes, such as logistic regression and other statistical machine learning tools (e.g., support vector machine, multilayer perceptron, random forest, deep belief network, decision tree, k-nearest neighbor, or LASSO) for automated audiometry and clinical predictions; convolutional neural networks for radiological image analysis; and large language models for automatic generation of diagnostic reports. Despite the advances in AI technologies, different ethical and professional challenges are still present, underscoring the need for larger, more diverse data collection and bioethics studies in the field of audiology.

Keywords: artificial intelligence; audiology; diagnostic tools; hearing tests; machine learning.

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Conflict of interest statement

The authors declare no conflicts of interest.

Figures

Figure 1
Figure 1
PRISMA diagram of the present review from database search to inclusion.
Figure 2
Figure 2
World map depicting top three contributing countries and timeline showing trends of contributions over the last decades. Abbreviation: manuscripts (MM).
Figure 3
Figure 3
Integration of AI in audiology and vestibology.
See this image and copyright information in PMC

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