中国口腔医学继续教育杂志 ›› 2025, Vol. 28 ›› Issue (4): 213-219.DOI: 10.12337/zgkqjxjyzz.2025.04.005

• 综述 • 上一篇    下一篇

人工智能在牙周病领域中的应用:现状、挑战与未来展望

李哲, 李琛*, 潘亚萍*   

  1. 中国医科大学附属口腔医院牙周病科,辽宁省口腔疾病重点实验室
  • 出版日期:2025-07-31 发布日期:2025-07-31
  • 通讯作者: *潘亚萍,联系方式:024-31927706,电子邮箱:yppan@cmu.edu.cn,通讯地址:沈阳市和平区南京北街117号,110002;李琛,联系方式:024-31927706,电子邮箱:lichen@cmu.edu.cn,通讯地址:沈阳市和平区南京北街117号,110002
  • 基金资助:
    国家科技部重点研发计划项目(编号2023YFC2506302)

Applications of Artificial Intelligence in Periodontal Disease: Current Status, Challenges, and Future Prospects

Zhe Li, Chen Li*, Yaping Pan*   

  1. Department of Periodontology, School and Hospital of Stomatology, China Medical University, Liaoning Provincial Key Laboratory of Oral Diseases, Shenyang, Liaoning Province, P.R. China
  • Online:2025-07-31 Published:2025-07-31
  • Contact: Yaping Pan. Tel: 024-31927706. Email: yppan@cmu.edu.cn. Address: No. 117 Nanjing North Street, Heping District, Shenyang 110002, Liaoning Province, P.R. China; Chen Li, Contact Phone: 13998145642. Email: lichen@cmu.edu.cn. Address: No. 117 Nanjing North Street, Heping District, Shenyang 110002, Liaoning Province, P.R. China.
  • Supported by:
    National Key Research and Development Program of the Ministry of Science and Technology of China (No.2023YFC2506302).

摘要: 牙周病作为一种常见的慢性炎症性口腔疾病,不仅会导致牙齿松动、脱落,影响咀嚼功能和面部美观等局部危害,还与多种全身疾病存在关联。牙周病的发生发展受诸多局部因素和全身因素影响,其风险评估和预后判断较为复杂。人工智能具备强大的数据处理能力,能够从多维数据中挖掘复杂规律,有望为牙周病的早期识别、风险预测和个性化治疗等提供新的思路和方法。本文系统梳理人工智能模型在牙周炎诊断、预后判断及科普与教学工作中的应用现状,并深入分析各类模型的优势与不足,旨在促进模型优化,为人工智能更好的应用于牙周相关的临床和教学领域提供参考。

关键词: 牙周病, 人工智能, 机器学习, 深度学习, 个性化治疗

Abstract: Periodontal disease, a common chronic inflammatory condition of the oral cavity, not only causes localized damage such as tooth mobility, tooth loss, impairing chewing function and facial aesthetics, but is also associated with a variety of systemic diseases. Its onset and progression are influenced by a complex interplay of both local and systemic factors, making its risk assessment and prognosis particularly challenging. Artificial intelligence (AI), with its powerful data processing capabilities, can uncover complex patterns from multidimensional data, offering new approaches for early detection, risk prediction, and personalized treatment of periodontal disease. This paper provides a comprehensive review of the current applications of AI models in the diagnosis and prognosis of periodontitis, as well as in public education and academic training. It also offers an in-depth analysis of the strengths and limitations of different AI models, aiming to support model optimization and promote more effective integration of AI into periodontal clinical practice and education.

Key words: periodontal disease, artificial intelligence, machine learning, deep learning, personalized treatment