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牙周炎分类的人工智能模型:系统审查

Jiaming Zhang1, Shuzhi Deng1, Ting Zou1

  • 1Shenzhen Stomatology Hospital (Pingshan) of Southern Medical University, Shenzhen, Guangdong, China; Shenzhen Clinical College of Stomatology, School of Stomatology, Southern Medical University, Shenzhen, Guangdong, China.

Journal of dentistry
|March 19, 2025
PubMed
概括
此摘要是机器生成的。

人工智能 (AI) 模型在分类牙周炎方面表现有前途,达到70%以上的准确性. 需要进一步发展,以解决临床使用的数据质量,可解释性和伦理问题.

关键词:
人工智能的人工智能是人工智能.分类 分类 分类 分类.卷积神经网络是一种卷积神经网络.深度学习是一种深度学习.机器学习 机器学习牙周病是指牙周病的发生.

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科学领域:

  • 牙科诊断 牙科诊断 牙科诊断
  • 医学中的人工智能.
  • 牙周病学 牙周病学

背景情况:

  • 牙周炎的诊断给牙医带来了一些挑战.
  • 准确的分类对于有效的治疗计划至关重要.

研究的目的:

  • 系统地审查人工智能 (AI) 模型在牙周炎分类方面的表现.
  • 评估AI在牙周炎检测中的诊断准确性和潜在的临床实用性.

主要方法:

  • 在主要数据库中进行了系统的文献搜索,直到2024年4月.
  • 包括专注于用于牙周炎分类的AI应用的研究.
  • 分析了来自28篇选定的文章的数据,评估了10个映射参数.

主要成果:

  • 人工智能模型的诊断准确度相当于牙医的诊断准确度,在牙周炎分类中超过70%.
  • 一些人工智能模型的诊断准确度在80-90%之间.
  • 精度因牙周炎的阶段而异.

结论:

  • 人工智能为牙周炎分类提供了一种新可靠的方法,有助于诊断效率.
  • 关键的挑战包括数据质量,模型解释性,概括性和道德考虑.
  • 人工智能有可能改善牙科诊断,远程医疗和家庭自我测试.