A review of deep learning in dentistry

被引:31
|
作者
Huang, Chenxi [1 ]
Wang, Jiaji [2 ]
Wang, Shuihua [2 ]
Zhang, Yudong [2 ,3 ]
机构
[1] Xiamen Univ, Sch Informat, Xiamen 361005, Peoples R China
[2] Univ Leicester, Sch Comp & Math Sci, Leicester LE1 7RH, England
[3] King Abdulaziz Univ, Fac Comp & Informat Technol, Dept Informat Syst, Jeddah 21589, Saudi Arabia
基金
英国生物技术与生命科学研究理事会;
关键词
Deep learning; Oral diseases; Image segmentation; Image classification; ARTIFICIAL-INTELLIGENCE; INTRAORAL PHOTOS; SEGMENTATION; RADIOGRAPHS; CARIES; TOMOGRAPHY; NETWORKS; MACHINE; CHINA; MODEL;
D O I
10.1016/j.neucom.2023.126629
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Oral diseases have a significant impact on human health, often going unnoticed in their early stages. Deep learning, a promising field in artificial intelligence, has shown remarkable success in various domains, especially dentistry. This paper aims to provide an overview of recent research on deep learning applications in dentistry, with a focus on dental imaging. Deep learning algorithms perform well in difficult tasks such as image segmentation and recognition, enabling accurate identification of oral conditions and abnormalities. Integration of deep learning with other oral health data offers a holistic understanding of the relationship between oral and systemic health. However, there are still many challenges that need to be addressed.
引用
收藏
页数:13
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