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利用基于人工智能的方法革新龋齿诊断。

Revolutionizing the diagnosis of dental caries using artificial intelligence-based methods.

作者信息

Marwaha Jasmine, Singla Mamta, Nath Amar, Arya Ashtha

机构信息

Department of Conservative Dentistry and Endodontics, SGT Dental College, Hospital and Research Institute, SGT University, Gurugram, Haryana, India.

Department of Computer Sciences and Engineering, Sant Longowal Institute of Engineering and Technology, Sangrur, Punjab, India.

出版信息

J Conserv Dent Endod. 2025 May;28(5):401-405. doi: 10.4103/JCDE.JCDE_172_25. Epub 2025 May 6.

DOI:10.4103/JCDE.JCDE_172_25
PMID:40463673
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC12129285/
Abstract

Early diagnosis and carious lesion detection through artificial intelligence (AI) have transformed current standard methodologies because it generates precise results which work more efficiently and dependably. AI uses machine learning and deep learning technologies with computer-aided diagnostic systems to accomplish exceptional image evaluation of radiographic data and clinical records in dental caries detection through intraoral scans. This review discusses both prevailing challenges which limit and potential future uses of AI in dental diagnosis together with its ability to become a part of standard clinical work routines. Various researchers confirmed that AI works as a helpful tool which supports dental experts by improving diagnosis and minimizing human biases to enhance preventive care effects for patients.

摘要

通过人工智能(AI)进行早期诊断和龋损检测已经改变了当前的标准方法,因为它能产生精确的结果,工作效率更高且更可靠。人工智能利用机器学习和深度学习技术以及计算机辅助诊断系统,通过口腔内扫描对龋齿检测中的放射影像数据和临床记录进行出色的图像评估。这篇综述讨论了限制人工智能在牙科诊断中应用的当前挑战、其未来的潜在用途,以及它成为标准临床工作流程一部分的能力。众多研究人员证实,人工智能是一种有用的工具,可通过改善诊断和最大限度减少人为偏差来支持牙科专家,从而增强对患者的预防保健效果。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/89a4/12129285/f9e15e8e9b81/JCDE-28-401-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/89a4/12129285/491c01b20fef/JCDE-28-401-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/89a4/12129285/f9e15e8e9b81/JCDE-28-401-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/89a4/12129285/491c01b20fef/JCDE-28-401-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/89a4/12129285/f9e15e8e9b81/JCDE-28-401-g002.jpg

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本文引用的文献

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Deep caries detection using deep learning: from dataset acquisition to detection.使用深度学习进行深龋检测:从数据集采集到检测
Clin Oral Investig. 2024 Dec 2;28(12):677. doi: 10.1007/s00784-024-06068-5.
2
Enhancement of early proximal caries annotations in radiographs: introducing the Diagnostic Insights for Radiographic Early-caries with micro-CT (ACTA-DIRECT) dataset.增强放射影像中早期近中龋的标注:介绍基于微计算机断层扫描的放射影像早期龋诊断洞察(ACTA-DIRECT)数据集。
BMC Oral Health. 2024 Oct 30;24(1):1325. doi: 10.1186/s12903-024-05076-x.
3
The Use of Artificial Intelligence in Caries Detection: A Review.
人工智能在龋齿检测中的应用:综述
Bioengineering (Basel). 2024 Sep 18;11(9):936. doi: 10.3390/bioengineering11090936.
4
Artificial Intelligence in Dental Caries Diagnosis and Detection: An Umbrella Review.人工智能在龋齿诊断和检测中的应用:一项伞状综述。
Clin Exp Dent Res. 2024 Aug;10(4):e70004. doi: 10.1002/cre2.70004.
5
Artificial intelligence……. A futuristic tool for advanced endodontics.人工智能……先进牙髓病学的未来工具。
J Conserv Dent Endod. 2024 May;27(5):447-448. doi: 10.4103/JCDE.JCDE_171_24. Epub 2024 May 10.
6
Validation of artificial intelligence application for dental caries diagnosis on intraoral bitewing and periapical radiographs.验证口腔内咬片和根尖片上用于龋齿诊断的人工智能应用。
J Dent. 2024 Aug;147:105105. doi: 10.1016/j.jdent.2024.105105. Epub 2024 May 29.
7
AI-Dentify: deep learning for proximal caries detection on bitewing x-ray - HUNT4 Oral Health Study.AI-Dentify:基于深度学习的咬合翼片 X 光龋齿近中检测 - HUNT4 口腔健康研究。
BMC Oral Health. 2024 Mar 18;24(1):344. doi: 10.1186/s12903-024-04120-0.
8
Artificial intelligence for radiographic imaging detection of caries lesions: a systematic review.人工智能在放射影像学龋病检测中的应用:系统评价。
BMC Oral Health. 2024 Feb 24;24(1):274. doi: 10.1186/s12903-024-04046-7.
9
Artificial intelligence in conservative dentistry and endodontics: A game-changer.保守牙科与牙髓病学中的人工智能:变革者。
J Conserv Dent Endod. 2023 Sep-Oct;26(5):514-518. doi: 10.4103/JCDE.JCDE_7_23. Epub 2023 Sep 16.
10
Transforming Dental Caries Diagnosis Through Artificial Intelligence-Based Techniques.通过基于人工智能的技术变革龋齿诊断
Cureus. 2023 Jul 11;15(7):e41694. doi: 10.7759/cureus.41694. eCollection 2023 Jul.