Marta Revilla-León DDS, MSD, PhD, Panagiotis Ntovas DDS, Abdul Basir Barmak MD, MSc, EdD, Miguel Gómez-Polo DDS, PhD
{"title":"Accuracy of artificial intelligence-based functions in intraoral scanners: A systematic review","authors":"Marta Revilla-León DDS, MSD, PhD, Panagiotis Ntovas DDS, Abdul Basir Barmak MD, MSc, EdD, Miguel Gómez-Polo DDS, PhD","doi":"10.1016/j.prosdent.2026.07.013","DOIUrl":null,"url":null,"abstract":"<div><h3>Statement of problem</h3><div>Artificial intelligence (AI)-based applications have increasingly been developed and integrated in different digital data acquisition technologies, including intraoral scanners (IOSs). A comprehensive evaluation of their accuracy and current state is lacking.</div></div><div>Artificial intelligence (AI)-based applications have increasingly been developed and integrated in different digital data acquisition technologies, including intraoral scanners (IOSs). A comprehensive evaluation of their accuracy and current state is lacking.</div><div><h3>Purpose</h3><div>The purpose of this systematic review was to evaluate the accuracy of AI-based applications integrated within IOSs to optimize digital data acquisition.</div></div><div>The purpose of this systematic review was to evaluate the accuracy of AI-based applications integrated within IOSs to optimize digital data acquisition.</div><div><h3>Material and methods</h3><div>A literature search was completed in 4 databases: PubMed/Medline, Embase, Web of Science, and Cochrane. A manual search was also conducted. Studies evaluating the accuracy of AI-based applications in IOSs to optimize the scanning process were included. Two investigators evaluated the studies independently by applying the Joanna Briggs Institute critical appraisal. A third examiner was consulted to resolve any lack of consensus. The included articles were organized based on the AI-based applications tested: AI cleaning, automatic alignment with implant scan body (ISB) computer-aided design (CAD) file, and occlusal collisions correction of articulated scans in maximum intercuspation position (MIP).</div></div><div>A literature search was completed in 4 databases: PubMed/Medline, Embase, Web of Science, and Cochrane. A manual search was also conducted. Studies evaluating the accuracy of AI-based applications in IOSs to optimize the scanning process were included. Two investigators evaluated the studies independently by applying the Joanna Briggs Institute critical appraisal. A third examiner was consulted to resolve any lack of consensus. The included articles were organized based on the AI-based applications tested: AI cleaning, automatic alignment with implant scan body (ISB) computer-aided design (CAD) file, and occlusal collisions correction of articulated scans in maximum intercuspation position (MIP).</div><div><h3>Results</h3><div>Seven articles were included. One study evaluated an AI-assisted scanning application and reported an overall improvement in scanning accuracy, evidenced by a lower root mean square (RMS) error in complete arch scans. Two studies assessed AI-based ISB file registration and reported conflicting results, with 1 study demonstrating improved accuracy and the other reporting reduced accuracy. However, differences in ISB design and implant scanning techniques were present among these studies. Finally, 4 studies evaluated occlusal collision correction; 3 reported improved MIP accuracy in completely dentate patients, whereas the remaining study reported variable outcomes depending on the extent of partial edentulism.</div></div><div>Seven articles were included. One study evaluated an AI-assisted scanning application and reported an overall improvement in scanning accuracy, evidenced by a lower root mean square (RMS) error in complete arch scans. Two studies assessed AI-based ISB file registration and reported conflicting results, with 1 study demonstrating improved accuracy and the other reporting reduced accuracy. However, differences in ISB design and implant scanning techniques were present among these studies. Finally, 4 studies evaluated occlusal collision correction; 3 reported improved MIP accuracy in completely dentate patients, whereas the remaining study reported variable outcomes depending on the extent of partial edentulism.</div><div><h3>Conclusions</h3><div>The available scientific evidence supporting these AI‑based applications remains limited. The performance of these AI‑based applications appears to be limited to the specific IOS system and generation evaluated and demonstrated variable performance depending on their intended function.</div></div><div>The available scientific evidence supporting these AI‑based applications remains limited. The performance of these AI‑based applications appears to be limited to the specific IOS system and generation evaluated and demonstrated variable performance depending on their intended function.</div>","PeriodicalId":16866,"journal":{"name":"Journal of Prosthetic Dentistry","volume":"136 4","pages":"Pages 997-1007"},"PeriodicalIF":5.6000,"publicationDate":"2026-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Prosthetic Dentistry","FirstCategoryId":"3","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0022391326005172","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2026/8/19 0:00:00","PubModel":"Epub","JCR":"Q1","JCRName":"DENTISTRY, ORAL SURGERY & MEDICINE","Score":null,"Total":0}
引用次数: 0
Abstract
Statement of problem
Artificial intelligence (AI)-based applications have increasingly been developed and integrated in different digital data acquisition technologies, including intraoral scanners (IOSs). A comprehensive evaluation of their accuracy and current state is lacking.
Artificial intelligence (AI)-based applications have increasingly been developed and integrated in different digital data acquisition technologies, including intraoral scanners (IOSs). A comprehensive evaluation of their accuracy and current state is lacking.
Purpose
The purpose of this systematic review was to evaluate the accuracy of AI-based applications integrated within IOSs to optimize digital data acquisition.
The purpose of this systematic review was to evaluate the accuracy of AI-based applications integrated within IOSs to optimize digital data acquisition.
Material and methods
A literature search was completed in 4 databases: PubMed/Medline, Embase, Web of Science, and Cochrane. A manual search was also conducted. Studies evaluating the accuracy of AI-based applications in IOSs to optimize the scanning process were included. Two investigators evaluated the studies independently by applying the Joanna Briggs Institute critical appraisal. A third examiner was consulted to resolve any lack of consensus. The included articles were organized based on the AI-based applications tested: AI cleaning, automatic alignment with implant scan body (ISB) computer-aided design (CAD) file, and occlusal collisions correction of articulated scans in maximum intercuspation position (MIP).
A literature search was completed in 4 databases: PubMed/Medline, Embase, Web of Science, and Cochrane. A manual search was also conducted. Studies evaluating the accuracy of AI-based applications in IOSs to optimize the scanning process were included. Two investigators evaluated the studies independently by applying the Joanna Briggs Institute critical appraisal. A third examiner was consulted to resolve any lack of consensus. The included articles were organized based on the AI-based applications tested: AI cleaning, automatic alignment with implant scan body (ISB) computer-aided design (CAD) file, and occlusal collisions correction of articulated scans in maximum intercuspation position (MIP).
Results
Seven articles were included. One study evaluated an AI-assisted scanning application and reported an overall improvement in scanning accuracy, evidenced by a lower root mean square (RMS) error in complete arch scans. Two studies assessed AI-based ISB file registration and reported conflicting results, with 1 study demonstrating improved accuracy and the other reporting reduced accuracy. However, differences in ISB design and implant scanning techniques were present among these studies. Finally, 4 studies evaluated occlusal collision correction; 3 reported improved MIP accuracy in completely dentate patients, whereas the remaining study reported variable outcomes depending on the extent of partial edentulism.
Seven articles were included. One study evaluated an AI-assisted scanning application and reported an overall improvement in scanning accuracy, evidenced by a lower root mean square (RMS) error in complete arch scans. Two studies assessed AI-based ISB file registration and reported conflicting results, with 1 study demonstrating improved accuracy and the other reporting reduced accuracy. However, differences in ISB design and implant scanning techniques were present among these studies. Finally, 4 studies evaluated occlusal collision correction; 3 reported improved MIP accuracy in completely dentate patients, whereas the remaining study reported variable outcomes depending on the extent of partial edentulism.
Conclusions
The available scientific evidence supporting these AI‑based applications remains limited. The performance of these AI‑based applications appears to be limited to the specific IOS system and generation evaluated and demonstrated variable performance depending on their intended function.
The available scientific evidence supporting these AI‑based applications remains limited. The performance of these AI‑based applications appears to be limited to the specific IOS system and generation evaluated and demonstrated variable performance depending on their intended function.
问题陈述:基于人工智能(AI)的应用程序越来越多地被开发并集成到不同的数字数据采集技术中,包括口内扫描仪(ios)。缺乏对其准确性和现状的全面评估。目的:本系统综述的目的是评估集成在ios中的基于人工智能的应用程序的准确性,以优化数字数据采集。材料和方法:在PubMed/Medline、Embase、Web of Science和Cochrane 4个数据库中完成文献检索。还进行了人工搜索。包括评估基于人工智能的应用程序在ios中优化扫描过程的准确性的研究。两名调查人员通过应用乔安娜布里格斯研究所的批判性评估来独立评估这些研究。咨询了第三位审查员,以解决任何缺乏共识的问题。纳入的文章是根据测试的基于人工智能的应用进行组织的:人工智能清洁,与种植体扫描体(ISB)计算机辅助设计(CAD)文件的自动对准,以及最大间歇位置(MIP)铰接扫描的咬合碰撞校正。结果:纳入7篇文章。一项研究评估了人工智能辅助扫描应用程序,并报告了扫描精度的总体提高,证明了全弓扫描的均方根误差(RMS)较低。两项研究评估了基于人工智能的ISB档案注册,并报告了相互矛盾的结果,其中一项研究表明准确性提高,另一项研究报告准确性降低。然而,在这些研究中,ISB设计和植入物扫描技术存在差异。最后,4项研究评估了咬合碰撞矫正;3项研究报告了全齿患者MIP准确性的提高,而其余研究报告了取决于部分全齿程度的可变结果。结论:支持这些基于人工智能的应用的现有科学证据仍然有限。这些基于人工智能的应用程序的性能似乎仅限于特定的IOS系统,并根据其预期功能生成评估和演示的可变性能。
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.