Reyes Lilian Toledo, Knorst Jessica Klöckner, Ortiz Fernanda Ruffo, Ardenghi Thiago Machado
Department of Stomatology, School of Dentistry, Federal University of Santa Maria, Santa Maria, Brazil.
J Clin Transl Res. 2021 Jul 30;7(4):523-539. eCollection 2021 Aug 26.
Machine learning (ML) has emerged as a branch of artificial intelligence dealing with the analysis of large amounts of data. The applications of ML algorithms have also expanded to health care, including dentistry. Recent advances in this field point to future improvements in diagnostic techniques and the prognosis of various diseases of the teeth and other maxillofacial structures.
The aim of this literature review is to describe the basis for ML being applied to different dental sub-fields in recent years, to identify typical algorithms used in the studies, and to summarize the scope and challenges of using these techniques in dental clinical practice.
The proficiency of emerging technologies that have begun to show encouraging results in the diagnosis and prognosis of oral diseases can improve the precision in the selection of treatment for patients. It is necessary to understand the challenges associated with using these tools to effectively use them in dental services and ensure a higher quality of care for patients.
机器学习（ML）已成为人工智能的一个分支，致力于处理大量数据分析。ML算法的应用也已扩展到医疗保健领域，包括牙科。该领域的最新进展预示着牙齿及其他颌面结构各种疾病的诊断技术和预后将在未来得到改善。
本综述的目的是描述近年来ML应用于不同牙科子领域的基础，确定研究中使用的典型算法，并总结在牙科临床实践中使用这些技术的范围和挑战。
新兴技术已开始在口腔疾病的诊断和预后方面显示出令人鼓舞的结果，其熟练应用可提高患者治疗选择的精准度。有必要了解使用这些工具所面临的挑战，以便在牙科服务中有效利用它们，并确保为患者提供更高质量的护理。
