人工智能在牙科领域的发展综述

Maryam Ghaffari , Yi Zhu , Annie Shrestha
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引用次数: 0

摘要

人工智能(AI)在医疗保健领域的应用已有几十年的历史,它有可能解决多种临床问题,使临床医生的工作变得更加轻松,从而彻底改变牙科医学。研究人工智能在牙周病和心脏病学中的应用尤为重要,因为这是牙科健康的两大关注领域。牙周病会影响牙齿周围的牙龈和牙槽骨,是成年人牙齿脱落的主要原因。龋齿学是对蛀牙的研究,也是人工智能研究的一个重要关注领域。人工智能算法可用于分析牙科图像,检测人类牙医可能会忽略的早期蛀牙迹象。这篇综述首先讨论了人工智能在医疗保健领域的历史,然后重点介绍了技术改进牙科的一些方法,接着描述了一些基本的人工智能模型,如人工神经网络(ANN)、卷积神经网络(CNN)和随机森林。随后,文章深入探讨了人工智能在牙周病、牙体病学、牙髓病学、修复学和正畸学中的应用,包括对不同类型的牙周病进行分类、识别骨质流失区域、确定疾病的严重程度、分析牙科图像以及检测疾病的早期征兆。另一方面,人工智能在牙科中的应用相对较少,因为在牙科中应用人工智能技术会带来一些挑战,要在牙科中成功应用人工智能技术,需要解决这些挑战。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A review of advancements of artificial intelligence in dentistry

Artificial intelligence (AI) has been used in healthcare for decades and has the potential to revolutionize dentistry by solving multiple clinical problems and making the work of clinicians easier. In particular, the study of AI applications in periodontal disease and cariology is important because these are two major areas of concern in dental health. Periodontal disease, which affects the gums and bone surrounding the teeth, is a major cause of tooth loss in adults. Cariology, the study of dental decay, is also an important area of focus for AI research. AI algorithms can be used to analyze dental images and detect early signs of decay that may be missed by human dentists. The review first discusses the history of AI in healthcare and then highlights some of the ways technology has improved dentistry and then describe some basic AI models such as artificial neural networks (ANNs), convolutional neural networks (CNNs), and random forest. The article then delves into how AI is involved in periodontal disease, cariology, endodontics, prosthodontics, and orthodontics including classifying different types of periodontal disease, identifying areas of bone loss, determining the severity of the disease, analyzing dental images, and detecting early signs of diseases. On the other hand, the application of AI in dentistry is relatively uncommon because implementing AI technologies in dentistry presents several challenges that need to be addressed for successful implementation of AI technologies in dentistry.

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