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相关概念视频

Anatomy of the Ear01:16

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Auditory sensation, commonly called hearing, involves the transformation of sonic waves into neural impulses facilitated by the structures of the auditory organ. The prominent, flesh-like structure on the side of the head, called the auricle, directs sound waves towards the auditory canal. The auricle is often mislabeled as the pinna, a term more aligned with mobile structures like a feline's external ear. The auditory canal penetrates the cranium via the external auditory meatus of the...
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Updated: Jul 15, 2025

Author Spotlight: Advancing CBCT and Digital Dental Image Integration with AI-Assisted Digitization
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基于图像的人工智能技术用于诊断中耳疾病:系统性审查

Dahye Song1, Taewan Kim1, Yeonjoon Lee1

  • 1Major in Bio Artificial Intelligence, Department of Applied Artificial Intelligence, Hanyang University, Ansan 15588, Republic of Korea.

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人工智能 (AI) 显示出使用医学成像诊断中耳炎的前景,比传统方法提高了准确性. 为了广泛的临床使用,需要进一步开发.

关键词:
人工智能的人工智能是人工智能.自动化诊断自动化诊断深度学习是一种深度学习.中耳疾病 中耳疾病.

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科学领域:

  • 耳鼻喉科 耳鼻喉科 耳鼻喉科
  • 医疗成像医学成像
  • 人工智能的人工智能

背景情况:

  • 传统的中耳炎诊断依赖于主观内镜评估,导致变化.
  • 人工智能 (AI) 提供客观的工具来提高诊断准确性和减少临床医生的偏见.

研究的目的:

  • 系统地审查用于医疗成像用于中耳炎诊断的AI技术.
  • 评估AI在耳鼻喉科的诊断性能,特别是对于中耳炎.

主要方法:

  • 来自五个主要数据库 (谷歌学者,PubMed,Medline,Embase,IEEE Xplore) 的研究的系统审查.
  • 纳入标准侧重于AI和使用医学成像的中耳炎诊断.
  • 排除与AI,中耳炎或缺乏医学成像组件无关的研究.

主要成果:

  • 在使用耳膜图像进行分类的26项研究中,平均准确率达到了86% (范围:48.7-99.16%).
  • 三项结合细分和分类的研究报告了平均准确率为90.8% (范围:88.06-93.9%).

结论:

  • 人工智能技术显示出改善中耳炎诊断的巨大潜力.
  • 人工智能的高诊断精度有利于远程医疗和初级保健,但为了患者安全,需要进一步提高性能.