口腔颌面外科杂志2025，Vol.35Issue(6)：438-447,10.DOI:10.12439/kqhm.1005-4979.2025.06.003
深度学习在检测牙周放射学骨丧失中的应用——系统评价与Meta分析
Application of deep learning in detecting periodontal radiographic bone loss:A systematic review and Meta-analysis
摘要
Abstract
Objective:To evaluate the accuracy of deep learning(DL)in detecting periodontal radiographic bone loss(RBL).Methods:A systematic search of the literature was conducted in PubMed,Scopus,Google Scholar,and Web of Science for relevant studies,the search covered the period from the inception of each database until March 2024,with language restrictions set to English.The Quality Assessment of Diagnostic Accuracy Studies-2(QUADAS-2)tool was used to assess the quality of the included studies.Results:A total of 19 articles meeting the criteria were included for full-text screening,with 8 of them being incorporated into the Meta-analysis.The Meta-analysis results showed that the DL models achieved a sensitivity of 0.84[95%confidence interval(CI)=0.79 to 0.90]and a specificity of 0.83(95%CI=0.75 to 0.91)in the classification of periodontitis.The summary receiver operating characteristic-area under the curve(SROC-AUC)was 0.92(95%CI=0.89 to 0.94).Conclusion:DL models demonstrate good accuracy and sensitivity in detecting periodontal RBL.关键词
牙周病/深度学习/放射学骨丧失/卷积神经网络Key words
periodontal diseases/deep learning/radiographic bone loss/convolutional neural networks分类
医药卫生引用本文复制引用
段晖,鲁嘉韦,贺梦柯,罗礼君..深度学习在检测牙周放射学骨丧失中的应用——系统评价与Meta分析[J].口腔颌面外科杂志,2025,35(6):438-447,10.基金项目
上海市卫生健康委员会面上项目(202240196) （202240196）
