山东大学耳鼻喉眼学报 ›› 2026, Vol. 40 ›› Issue (1): 112-119.doi: 10.6040/j.issn.1673-3770.0.2023.470

• 综述 • 上一篇    

深度学习技术在咽喉内镜应用中的研究进展及前景分析

程卓1,2, 梁辉2, 邢鲁民3   

  1. 山东省医学科学院)耳鼻咽喉头颈外科, 山东 济南 250021;
    2.山东第一医科大学第一附属医院(山东省千佛山医院)耳鼻咽喉头颈外科, 山东 济南 250014;
    3.山东第一医科大学第一附属医院(山东省千佛山医院)信息中心, 山东 济南 250014
  • 发布日期:2026-02-13
  • 通讯作者: 梁辉. E-mail:onlinelh@163.com

Research progress and prospect analysis of deep learning technology in the application of pharyngeal and laryngeal endoscopy

CHENG Zhuo1,2, LIANG Hui2, XING Lumin3   

  1. 1. Department of Otorhinolaryngology & Head and Neck Surgery, Shandong First Medical University & Shandong Academy of Medical Sciences, Jinan 250021, Shandong, China2. Department of Otorhinolaryngology & Head and Neck Surgery, The First Affiliated Hospital of Shandong First Medical University & Shandong Provincial Qianfoshan Hospital, Jinan 250014, Shandong, China3. Department of Information, The First Affiliated Hospital of Shandong First Medical University & Shandong Provincial Qianfoshan Hospital, Shandong, Jinan 250014, Shandong, China
  • Published:2026-02-13

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摘要： 深度学习的出现对医疗水平特别是医学检查的进步起到了巨大的推动作用,耳鼻咽喉头颈外科部分领域亦因此获益,基于深度学习的咽喉内镜检查数据分析领域近5年来做出了极有成效的尝试。本文以近5年基于深度学习的咽喉内镜应用及相关研究作为讨论主体,分析该领域的研究进程并将其发展阶段划分为神经网络萌芽阶段、神经网络与医学的交融和适用性发展的神经网络阶段三个阶段;以临床、样本信息、其他三个方面分别讨论现阶段研究瓶颈,并阐述了未来可能的解决方案及发展前景,指出了当前咽喉内镜中深度学习应用的主要障碍,并给出了未来多中心研究、多任务学习、高水平信息数据采集等可能的发展趋势展望。

关键词: 咽喉内镜, 人工智能, 深度学习, 耳鼻咽喉头颈外科学, 计算机辅助诊断

Abstract: The emergence of deep learning has played a huge role in the promotion of medical quality, especially in the advancement of medical examination, and some areas of otolaryngology and head and neck surgery have benefited from it. On the basis of deep learning, the field of endoscopic analysis of the pharynx and larynx has made very effective attempts in the past five years. This article discusses the research and related research based on deep learning in pharyngeal and laryngeal endoscopic application in the past five years, analyzes the research progress in this field, and divides its development stage into three stages: the stage of neural network germination, the blending of neural network and medicine, and the development of neural network applicability. Based on clinical, sample information and other three aspects, this article discusses current research bottlenecks, expounds possible solutions and development prospects in the future, points out the main obstacles in the application of deep learning in current pharyngeal and laryngeal endoscopic research, and gives a possible development trend outlook in multiple aspects such as multicenter research, multitask learning, high-level data information collection in the future.

Key words: Pharyngeal and laryngeal endoscopy, artificial Intelligence, deep learning, Otorhinolaryngology head and neck surgery, Computer-assisted diagnosis

中图分类号: 

  • R762
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