Automated diagnosis using artificial intelligence a step forward for preventive dentistry: A systematic review

Q4 Dentistry Revista Romana de Stomatologie Pub Date : 2022-09-30 DOI:10.37897/rjs.2022.3.7
Radu Chifor, Tudor Arsenescu, Laura Monica Dascalu (Rusu), A. Badea
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Abstract

Background. Early diagnosis and monitoring the evolution of the patients is required to be able to have effective preventive attitudes. An easy and cost-effective way of diagnosis is needed for this purpose. The aim of the study was to evaluate the AI level of use in dentistry diagnosis and the fields of its applicability especially for early diagnosis purposes. A secondary objective was to point out the measured performances for automated AI diagnosis by comparison with standard diagnosis procedures. Material and methods. A comprehensive electronic search was performed in November 2022 through PubMed, Scopus, and Web of Science databases. The following keywords were used to search the databases: (”Artificial Intelligence” OR ”neural network” OR ”Deep learning” OR “Machine learning”) AND (”Dentistry” OR “Dental medicine”) AND (” periodontal disease” OR ”periodontics” OR ”Carious lesions” OR ”oral cancer” OR ”restorative” or “early diagnosis”). The risk of bias (RoB) of the included studies was assessed using PROBAST tool. Results. A total of 334 publications were collected after searching the databases. For 218 remaining publications the title and the abstract were assessed. The reviewers agreed to continue with 69 studies for full text assessment. Because 49 studies had not completely fulfilled the inclusion criteria only 20 publications were included in the final analysis. AI automatic data processing for diagnostic purposes was implemented in the field of dental radiology, oral pathology, restorative dentistry, pedodontics, oncology, endodontics, and periodontics. Conclusion. AI based automatic diagnostic is a powerful and reliable tool that has a great future potential for different fields of dental medicine like periodontal disease, oral cancer, and carious lesions.
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使用人工智能的自动诊断是预防性牙科的一个进步:系统回顾
背景。早期诊断和监测患者的演变是必须的,才能有有效的预防态度。为此,需要一种简便、经济的诊断方法。本研究的目的是评估人工智能在牙科诊断中的应用水平及其在早期诊断中的应用领域。第二个目标是通过与标准诊断程序的比较,指出自动人工智能诊断的测量性能。材料和方法。2022年11月,通过PubMed、Scopus和Web of Science数据库进行了全面的电子搜索。使用以下关键词搜索数据库:(“人工智能”或“神经网络”或“深度学习”或“机器学习”)和(“牙科”或“牙科医学”)和(“牙周病”或“牙周病”或“龋齿病变”或“口腔癌”或“恢复性”或“早期诊断”)。采用PROBAST工具评估纳入研究的偏倚风险(RoB)。结果。检索数据库后,共收集到334份出版物。对其余218份出版物的标题和摘要进行了评估。审稿人同意继续对69项研究进行全文评估。由于49项研究没有完全符合纳入标准,最终分析中只纳入了20篇论文。用于诊断目的的人工智能自动数据处理在牙科放射学、口腔病理学、修复牙科、儿科学、肿瘤学、牙髓学和牙周病领域得到了实施。结论。基于人工智能的自动诊断是一种强大而可靠的工具,在牙周病、口腔癌、龋齿等牙科医学的不同领域具有巨大的未来潜力。
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来源期刊
CiteScore
0.10
自引率
0.00%
发文量
21
审稿时长
4 weeks
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