Exploring the intersection of cochlear implants and artificial intelligence: A mixed-method systematic and scoping review

Intelligence-based medicine Pub Date : 2025-01-01 DOI:10.1016/j.ibmed.2025.100296

Aurenzo Gonçalves Mocelin , Pedro Angelo Basei de Paula , Daniel Tiepolo Kochinski , Thayná Cristina Wiezbicki , Rogério de Azevedo Hamerschmidt , Mayara Risnei Watanabe , Rogério Hamerschmidt

{"title":"Exploring the intersection of cochlear implants and artificial intelligence: A mixed-method systematic and scoping review","authors":"Aurenzo Gonçalves Mocelin , Pedro Angelo Basei de Paula , Daniel Tiepolo Kochinski , Thayná Cristina Wiezbicki , Rogério de Azevedo Hamerschmidt , Mayara Risnei Watanabe , Rogério Hamerschmidt","doi":"10.1016/j.ibmed.2025.100296","DOIUrl":null,"url":null,"abstract":"<div><h3>Objective</h3><div>This study systematically evaluates the role of artificial intelligence (AI) in cochlear implant (CI) technology, focusing on speech enhancement, automated fitting, AI-assisted surgery, predictive modeling, and rehabilitation. The review identifies key advancements, existing limitations, and areas for future development.</div></div><div><h3>Methods</h3><div>Following PRISMA guidelines, we conducted a systematic search across PubMed, IEEE Xplore, Scopus, ScienceDirect, and Embase. We included peer-reviewed primary data studies on AI applications in CIs. The selected studies were categorized into thematic subdomains, such as noise suppression, adaptive programming, AI-driven surgical planning, and telemedicine applications.</div></div><div><h3>Results</h3><div>From an initial pool of 743 records, 129 studies met the eligibility criteria and were included in the final analysis. These studies were categorized into eleven thematic subdomains. The review identified the main application areas and emerging research fronts at the intersection of artificial intelligence and cochlear implant technologies, including speech enhancement, automated fitting, predictive modeling, rehabilitation support, and AI-assisted surgery.</div></div><div><h3>Discussion and conclusion</h3><div>AI is transforming CI technology by improving speech perception, personalization, and surgical precision. However, challenges persist, including computational constraints, data heterogeneity, and the need for large-scale clinical validation. Future research should prioritize energy-efficient AI architectures, regulatory approval pathways, and ethical considerations in automated decision-making. Advancing AI-driven telemedicine solutions can expand CI accessibility, reducing the need for in-person programming. Addressing these challenges will accelerate the development of more adaptive and user-centered CI solutions, ultimately enhancing auditory rehabilitation and quality of life for CI users.</div></div>","PeriodicalId":73399,"journal":{"name":"Intelligence-based medicine","volume":"12 ","pages":"Article 100296"},"PeriodicalIF":0.0000,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Intelligence-based medicine","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2666521225001000","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}

引用次数: 0

Abstract

Objective

This study systematically evaluates the role of artificial intelligence (AI) in cochlear implant (CI) technology, focusing on speech enhancement, automated fitting, AI-assisted surgery, predictive modeling, and rehabilitation. The review identifies key advancements, existing limitations, and areas for future development.

Methods

Following PRISMA guidelines, we conducted a systematic search across PubMed, IEEE Xplore, Scopus, ScienceDirect, and Embase. We included peer-reviewed primary data studies on AI applications in CIs. The selected studies were categorized into thematic subdomains, such as noise suppression, adaptive programming, AI-driven surgical planning, and telemedicine applications.

Results

From an initial pool of 743 records, 129 studies met the eligibility criteria and were included in the final analysis. These studies were categorized into eleven thematic subdomains. The review identified the main application areas and emerging research fronts at the intersection of artificial intelligence and cochlear implant technologies, including speech enhancement, automated fitting, predictive modeling, rehabilitation support, and AI-assisted surgery.

Discussion and conclusion

AI is transforming CI technology by improving speech perception, personalization, and surgical precision. However, challenges persist, including computational constraints, data heterogeneity, and the need for large-scale clinical validation. Future research should prioritize energy-efficient AI architectures, regulatory approval pathways, and ethical considerations in automated decision-making. Advancing AI-driven telemedicine solutions can expand CI accessibility, reducing the need for in-person programming. Addressing these challenges will accelerate the development of more adaptive and user-centered CI solutions, ultimately enhancing auditory rehabilitation and quality of life for CI users.

查看原文本刊更多论文

探索人工耳蜗与人工智能的交叉：一种混合方法的系统和范围综述

目的系统评估人工智能（AI）在人工耳蜗（CI）技术中的作用，重点关注语音增强、自动验配、人工智能辅助手术、预测建模和康复。该审查确定了主要进展、现有限制和未来发展的领域。方法遵循PRISMA指南，我们在PubMed、IEEE explore、Scopus、ScienceDirect和Embase中进行了系统搜索。我们纳入了人工智能在ci中的应用的同行评议的原始数据研究。选定的研究被分类为主题子领域，如噪声抑制、自适应编程、人工智能驱动的手术计划和远程医疗应用。结果从最初的743份记录中，有129项研究符合资格标准，并被纳入最终分析。这些研究分为11个主题子领域。该综述确定了人工智能和人工耳蜗技术交叉的主要应用领域和新兴研究前沿，包括语音增强、自动装配、预测建模、康复支持和人工智能辅助手术。人工智能正在通过提高语音感知、个性化和手术精度来改变CI技术。然而，挑战依然存在，包括计算限制、数据异质性和大规模临床验证的需要。未来的研究应优先考虑节能的人工智能架构、监管审批途径和自动化决策中的道德考虑。推进人工智能驱动的远程医疗解决方案可以扩大CI的可访问性，减少对亲自编程的需求。解决这些挑战将加速开发更具适应性和以用户为中心的CI解决方案，最终提高CI用户的听觉康复和生活质量。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

求助全文

约1分钟内获得全文求助全文

来源期刊