Artificial intelligence for hearing loss prevention, diagnosis, and management

Abstract

This paper explores the transformative impact of artificial intelligence (AI), particularly machine learning (ML), on diagnosing and treating hearing loss, which affects over 5% of the global population across all ages and demographics. AI encompasses various applications, from natural language processing models like ChatGPT to image recognition systems; however, this paper focuses on ML, a subfield of AI that can revolutionize audiology by enhancing early detection, formulating personalized rehabilitation plans, and integrating electronic health records for streamlined patient care. The integration of ML into audiometry, termed "computational audiology," allows for automated, accurate hearing tests. AI algorithms can process vast data sets, provide detailed audiograms, and facilitate early detection of hearing impairments. Research shows ML's effectiveness in classifying audiograms, conducting automated audiometry, and predicting hearing loss based on noise exposure and genetics. These advancements suggest that AI can make audiological diagnostics and treatment more accessible and efficient. The future of audiology lies in the seamless integration of AI technologies. Collaborative efforts between audiologists, AI experts, and individuals with hearing loss are essential to overcome challenges and leverage AI's full potential. Continued research and development will enhance AI applications in audiology, improving patient outcomes and quality of life worldwide.

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