New developments in the application of artificial intelligence to laryngology.

IF 1.9 4区医学 Q2 OTORHINOLARYNGOLOGY

Current Opinion in Otolaryngology & Head and Neck Surgery Pub Date : 2024-12-01 Epub Date: 2024-07-24 DOI:10.1097/MOO.0000000000000999

Stefan R Torborg, Ashley Yeo Eun Kim, Anaïs Rameau

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引用次数: 0

Abstract

Purpose of review: The purpose of this review is to summarize the existing literature on artificial intelligence technology utilization in laryngology, highlighting recent advances and current barriers to implementation.

Recent findings: The volume of publications studying applications of artificial intelligence in laryngology has rapidly increased, demonstrating a strong interest in utilizing this technology. Vocal biomarkers for disease screening, deep learning analysis of videolaryngoscopy for lesion identification, and auto-segmentation of videofluoroscopy for detection of aspiration are a few of the new ways in which artificial intelligence is poised to transform clinical care in laryngology. Increasing collaboration is ongoing to establish guidelines and standards for the field to ensure generalizability.

Summary: Artificial intelligence tools have the potential to greatly advance laryngology care by creating novel screening methods, improving how data-heavy diagnostics of laryngology are analyzed, and standardizing outcome measures. However, physician and patient trust in artificial intelligence must improve for the technology to be successfully implemented. Additionally, most existing studies lack large and diverse datasets, external validation, and consistent ground-truth references necessary to produce generalizable results. Collaborative, large-scale studies will fuel technological innovation and bring artificial intelligence to the forefront of patient care in laryngology.

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人工智能在喉科应用方面的新进展。

综述目的：本综述旨在总结有关人工智能技术在喉科领域应用的现有文献，重点介绍最新进展和当前实施障碍：研究人工智能在喉科学中应用的论文数量迅速增加，表明了人们对利用这一技术的浓厚兴趣。用于疾病筛查的声乐生物标志物、用于病变识别的视频喉镜深度学习分析以及用于吸入检测的视频荧光透视自动分区是人工智能有望改变喉科临床护理的几种新方法。小结：人工智能工具通过创造新颖的筛查方法、改善喉科数据繁重的诊断分析方法以及标准化结果测量，有可能极大地推动喉科护理的发展。然而，要成功应用人工智能技术，必须提高医生和患者对人工智能的信任度。此外，大多数现有研究缺乏大型、多样化的数据集、外部验证和一致的地面实况参考，而这些都是产生可推广结果所必需的。大规模的合作研究将推动技术创新，并将人工智能带入喉科患者护理的最前沿。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Current Opinion in Otolaryngology & Head and Neck Surgery OTORHINOLARYNGOLOGY-

CiteScore

2.90

自引率

0.00%

发文量

审稿时长

6-12 weeks

期刊介绍： Current Opinion in Otolaryngology & Head and Neck Surgery is a bimonthly publication offering a unique and wide ranging perspective on the key developments in the field. Each issue features hand-picked review articles from our team of expert editors. With eleven disciplines published across the year – including maxillofacial surgery, head and neck oncology and speech therapy and rehabilitation – every issue also contains annotated references detailing the merits of the most important papers.