Scholarlink

<p>This narrative review explores the transformative role of artificial intelligence (AI) in the management of hearing loss, a highly prevalent global health concern. It synthesizes recent advancements across the hearing care continuum, from AI-enhanced screening tools that improve accessibility and efficiency, to diagnostic applications in audiometric analysis, otoscopy, and radiology that achieve specialist-level accuracy. The review details how AI enables highly personalized treatment through smart hearing aids and cochlear implants that adapt in real-time, and how it powers adaptive rehabilitation programs, immersive training environments, and remote monitoring platforms. Despite this promising progress, the integration of AI into clinical audiology faces significant challenges, including issues of data quality, model interpretability, regulatory hurdles, and ethical concerns regarding bias and privacy. The future of AI in hearing care hinges on developing explainable, federated learning models, creating multimodal datasets, and fostering interdisciplinary collaboration. Ultimately, a synergistic human-AI partnership is envisioned to advance hearing healthcare, making it more precise, efficient, and accessible worldwide.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Artificial Intelligence in Hearing Loss: A Narrative Review of Opportunities, Limitations and Future implications

  • 期刊论文

  • 发表日期：

    2026年2月28日

查看全文
  • Saurabh Varshney,
  • Pratima Gupta,
  • Rakhi Gaur,
  • Shiv Kumar Mudgal

摘要

This narrative review explores the transformative role of artificial intelligence (AI) in the management of hearing loss, a highly prevalent global health concern. It synthesizes recent advancements across the hearing care continuum, from AI-enhanced screening tools that improve accessibility and efficiency, to diagnostic applications in audiometric analysis, otoscopy, and radiology that achieve specialist-level accuracy. The review details how AI enables highly personalized treatment through smart hearing aids and cochlear implants that adapt in real-time, and how it powers adaptive rehabilitation programs, immersive training environments, and remote monitoring platforms. Despite this promising progress, the integration of AI into clinical audiology faces significant challenges, including issues of data quality, model interpretability, regulatory hurdles, and ethical concerns regarding bias and privacy. The future of AI in hearing care hinges on developing explainable, federated learning models, creating multimodal datasets, and fostering interdisciplinary collaboration. Ultimately, a synergistic human-AI partnership is envisioned to advance hearing healthcare, making it more precise, efficient, and accessible worldwide.