深度学习在种植体周围炎预测诊断中的应用研究进展

doi:10.13701/j.cnki.kqyxyj.2026.03.002

摘要/Abstract

摘要： 种植体周围炎风险因素复杂,早期临床症状隐匿,持续追踪种植体周围软硬组织动态有助于对疾病进程进行有效管理。深度学习作为新型人工智能技术应用于临床,可锁定病损部位进行高精度量化评估,自动学习患者相关数据推演病情发展,成为当前口腔种植领域的新型诊疗工具。本文就深度学习在监测种植体周围组织状况、种植体周围炎预测及诊断方面的应用与研究现状作一综述。

关键词: 人工智能, 深度学习, 口腔种植, 种植体周围炎

Abstract: Considering the complex clinical risk factors and the insidious initial manifestations of peri-implantitis, continuous monitoring of peri-implant soft and hard tissues is necessary for more effective disease management. Deep learning, as a rapidly evolving emerging artificial intelligence technology, has been deemed promising in oral implantology for detecting lesion sites, conducting quantitative evaluation, analyzing autonomous learning datasets, and deducing disease progression pathways. This article summarizes the application of deep learning in the assessment of peri-implant tissues as well as the prediction and diagnosis of peri-implantitis.

Key words: artificial intelligence, deep learning, oral implantology, peri-implantitis

王晓雯, 高莺. 深度学习在种植体周围炎预测诊断中的应用研究进展[J]. 口腔医学研究, 2026, 42(3): 186-190.

WANG Xiaowen, GAO Ying. Research Progress on Application of Deep Learning in Prediction and Diagnosis of Peri-implantitis[J]. Journal of Oral Science Research, 2026, 42(3): 186-190.

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