Abstract：
Machine learning (ML) has led to significant advances in dentistry, easing the workload of professionals and improving the performance of various medical processes. The fields of periodontology and implantology can profit from these advances for tasks such as determining periodontally compromised teeth, assisting doctors in the implant planning process, determining types of implants, or predicting the occurrence of peri-implantitis. The current paper provides an overview of recent ML techniques applied in periodontology and implantology, aiming to identify popular models for different medical tasks, to assess the impact of the training data on the success of the automatic algorithms and to highlight advantages and disadvantages of various approaches. 48 original research papers, published between 2016 and 2023, were selected and divided into four classes: periodontology, implant planning, implant brands and types, and success of dental implants. These papers were analyzed in terms of aim, technical details, characteristics of training and testing data, results, and medical observations. The purpose of this paper is not to provide an exhaustive survey, but to show representative methods from recent literature that highlight the advantages and disadvantages of various approaches, as well as the potential of applying machine learning in dentistry.
摘要：
机器学习(ML)在牙科领域取得了重大进展，减轻专业人员的工作量，提高各种医疗流程的性能。牙周学和种植学领域可以从这些进步中受益，例如确定牙周受损的牙齿，在植入规划过程中协助医生，确定植入物的类型，或预测种植体周围炎的发生。本文概述了近年来ML技术在牙周学和种植学中的应用。旨在识别不同医疗任务的流行模型，评估训练数据对自动算法成功的影响，并强调各种方法的优缺点。48篇原创研究论文，2016年至2023年出版，被选中并分为四类：牙周病，植入规划,植入物品牌和类型，以及牙科植入物的成功。这些论文是在目的方面进行分析的，技术细节,训练和测试数据的特征，结果，和医学观察。本文的目的不是提供详尽的调查，但要展示来自最近文献的代表性方法，突出各种方法的优缺点，以及将机器学习应用于牙科的潜力。
