Advancements in artificial intelligence algorithms for dental implant identification: A systematic review with meta-analysis

IF 4.8 2区 医学 Q1 DENTISTRY, ORAL SURGERY & MEDICINE Journal of Prosthetic Dentistry Pub Date : 2023-12-29 DOI:10.1016/j.prosdent.2023.11.027
Ahmed Yaseen Alqutaibi PhD , Radhwan S. Algabri PhD , Dina Elawady PhD , Wafaa Ibrahim Ibrahim PhD
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Abstract

Statement of problem

The evidence regarding the application of artificial intelligence (AI) in identifying dental implant systems is currently inconclusive. The available studies present varying results and methodologies, making it difficult to draw definitive conclusions.

Purpose

The purpose of this systematic review with meta-analysis was to comprehensively analyze and evaluate articles that investigate the application of AI in identifying and classifying dental implant systems.

Material and methods

An electronic systematic review was conducted across 3 databases: MEDLINE/PubMed, Cochrane, and Scopus. Additionally, a manual search was performed. The inclusion criteria consisted of peer-reviewed studies investigating the accuracy of AI-based diagnostic tools on dental radiographs for identifying and classifying dental implant systems and comparing the results with those obtained by expert judges using manual techniques—the search strategy encompassed articles published until September 2023. The Quality Assessment of Diagnostic Accuracy Studies-2 (QUADAS-2) tool was used to assess the quality of included articles.

Results

Twenty-two eligible articles were included in this review. These articles described the use of AI in detecting dental implants through conventional radiographs. The pooled data showed that dental implant identification had an overall accuracy of 92.56% (range 90.49% to 94.63%). Eleven studies showed a low risk of bias, 6 demonstrated some concern risk, and 5 showed a high risk of bias.

Conclusions

AI models using panoramic and periapical radiographs can accurately identify and categorize dental implant systems. However, additional well-conducted research is recommended to identify the most common implant systems.
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人工智能算法在牙科植入物识别方面的进步:系统回顾与荟萃分析
问题陈述 关于人工智能(AI)在牙科植入系统识别中的应用,目前尚无定论。本系统综述的目的是全面分析和评估研究人工智能在识别和分类牙科植入系统中应用的文章。材料和方法在 3 个数据库中进行了电子系统综述:材料和方法在 3 个数据库中进行了电子系统综述:MEDLINE/PubMed、Cochrane 和 Scopus。此外,还进行了人工检索。纳入标准包括同行评议的研究,这些研究调查了基于人工智能的诊断工具在牙科X光片上识别和分类牙科种植系统的准确性,并将结果与专家评委使用人工技术获得的结果进行了比较--检索策略涵盖了2023年9月之前发表的文章。诊断准确性研究质量评估-2(QUADAS-2)工具用于评估纳入文章的质量。这些文章介绍了人工智能在通过传统射线照片检测种植牙方面的应用。汇总数据显示,牙种植体识别的总体准确率为 92.56%(范围为 90.49% 至 94.63%)。11项研究显示偏倚风险较低,6项研究显示存在一定的风险,5项研究显示偏倚风险较高。然而,建议进行更多的研究,以确定最常见的种植系统。
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来源期刊
Journal of Prosthetic Dentistry
Journal of Prosthetic Dentistry 医学-牙科与口腔外科
CiteScore
7.00
自引率
13.00%
发文量
599
审稿时长
69 days
期刊介绍: The Journal of Prosthetic Dentistry is the leading professional journal devoted exclusively to prosthetic and restorative dentistry. The Journal is the official publication for 24 leading U.S. international prosthodontic organizations. The monthly publication features timely, original peer-reviewed articles on the newest techniques, dental materials, and research findings. The Journal serves prosthodontists and dentists in advanced practice, and features color photos that illustrate many step-by-step procedures. The Journal of Prosthetic Dentistry is included in Index Medicus and CINAHL.
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