中国口腔颌面外科杂志 ›› 2024, Vol. 22 ›› Issue (6): 605-610.doi: 10.19438/j.cjoms.2024.06.014

• 综述 • 上一篇    下一篇

机器学习在口腔医疗诊断中的应用进展

刘清海1,*, 刘廷廷2,*, 朱凌3#, 马坤宁4#   

  1. 1.上海中医药大学附属龙华医院 绩效管理部,上海 200032;
    2.上海交通大学化学化工学院,上海 200240;
    3.上海交通大学医学院附属第九人民医院 放射科,上海 201999;
    4.济南市口腔医院 正畸科,山东 济南 250022
  • 收稿日期:2024-06-26 修回日期:2024-07-25 出版日期:2024-11-20 发布日期:2024-12-11
  • 通讯作者: 朱凌,E-mail: puxuke12@126.com;马坤宁,E-mail:605754727@qq.com。#共同通信作者
  • 作者简介:刘清海(1991-),男,硕士,助理研究员,E-mail: lqhlonghua@163.com;刘廷廷(1998-),男,在读博士研究生,E-mail: sjtu-ltt@sjtu.edu.cn。*并列第一作者
  • 基金资助:
    上海申康医院发展中心临床科技创新项目(SHDC12021607)

Application progress of machine learning in oral medical diagnosis

LIU Qing-hai1, LIU Ting-ting2, ZHU Ling3, MA Kun-ning4   

  1. l. Department of Performance Management, Longhua Hospital Affiliated to Shanghai University of Traditional Chinese Medicine. Shanghai 200032;
    2. School of Chemistry and Chemical Engineering, Shanghai Jiao Tong University. Shanghai 200240;
    3. Department of Radiology, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine. Shanghai 201999;
    4. Department of Orthodontics, Jinan Stomatological Hospital. Jinan 250022, Shandong Province, China
  • Received:2024-06-26 Revised:2024-07-25 Online:2024-11-20 Published:2024-12-11

摘要: 随着人工智能技术的快速发展,机器学习已成为口腔医疗领域的重要工具。机器学习技术用于口腔疾病的诊断和分类,不仅提供了高效的患者风险评估与管理工具,还支持个性化的治疗计划和医疗方案制定。此外,机器学习在医学图像分析和解释方面也发挥了重要作用,能帮助医师快速准确地识别口腔病变和病变类型。本文介绍机器学习在口腔医疗诊断中的典型应用,并对其面临的技术挑战以及可能的解决方案进行讨论。

关键词: 机器学习, 口腔医疗, 疾病诊断, 风险评估, 个性化医疗, 医学图像分析

Abstract: With the rapid advancement of artificial intelligence technology, machine learning has become a vital tool in the field of oral healthcare. Machine learning technology for the diagnosis and classification of oral diseases not only provides efficient patient risk assessment and management tools, but also supports personalized treatment planning and medical protocol development. In addition, machine learning also plays an important role in medical image analysis and interpretation, helping physicians quickly and accurately identify oral lesions and their types. This article introduced typical applications of machine learning in oral medical diagnosis, and discussed the technical challenges and possible solutions.

Key words: Machine learning, Oral medicine, Disease diagnosis, Risk assessment, Personalized medicine, Medical image analysis

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