The role of artificial intelligence in implant dentistry: a systematic review.

International journal of oral and maxillofacial surgery Pub Date : 2025-05-28 DOI:10.1016/j.ijom.2025.04.005

G Vázquez-Sebrango, E Anitua, I Macía, I Arganda-Carreras

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Abstract

The aim of this systematic review was to comprehensively analyse recent studies on the application of artificial intelligence (AI) in dental implantology. The PRISMA guidelines were followed. Five databases were accessed: Scopus, Web of Science, MEDLINE/PubMed, IEEE Xplore, and JSTOR. Documents published between 2018 and October 15, 2024 relating to AI and implantology were considered. Exclusions encompassed reviews, opinion articles, books, conference references, studies using AI as a supplementary method, AI for teaching implant dentistry, and AI for implant fabrication, prothesis, or design. A total of 120 relevant papers were included. Risk of bias was assessed using PROBAST. Findings demonstrated extensive utilization of AI in various aspects of dental implantology: guided surgery, diagnosis, classification of oral structures, bone classification, classification of dental restorations, implant classification, implant planning, and implant prognosis. Deep learning algorithms were employed in 89.2% of studies, predominantly utilizing image data (72.0% two-dimensional images and 28.0% three-dimensional images). Publications doubled in 2022 compared to the previous year and have remained consistent since. Despite growth, the field remains relatively underdeveloped. However, with advancements in technology and data quality, substantial progress is anticipated in forthcoming years. Remarkably, 11 studies were found to have a high risk of bias.

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人工智能在种植牙科中的作用：系统综述。

本系统综述的目的是全面分析人工智能（AI）在口腔种植学中的应用的最新研究。遵循了PRISMA准则。5个数据库被访问：Scopus， Web of Science, MEDLINE/PubMed， IEEE explore和JSTOR。2018年至2024年10月15日期间发表的有关人工智能和植入学的文件被考虑在内。排除包括评论、评论文章、书籍、会议参考文献、使用人工智能作为补充方法的研究、人工智能用于种植牙科教学、人工智能用于种植体制造、假体或设计。共收录相关论文120篇。使用PROBAST评估偏倚风险。研究结果表明，人工智能广泛应用于牙科种植的各个方面：指导手术、诊断、口腔结构分类、骨分类、牙体修复分类、种植体分类、种植体规划和种植体预后。89.2%的研究采用了深度学习算法，主要利用图像数据（72.0%的二维图像和28.0%的三维图像）。与前一年相比，2022年的出版物增加了一倍，此后一直保持不变。尽管有所增长，但该领域仍相对不发达。然而，随着技术和数据质量的进步，预计未来几年将取得实质性进展。值得注意的是，有11项研究存在高偏倚风险。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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International journal of oral and maxillofacial surgery

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