Evaluating the Artificial Intelligence Driven Monitoring System Notifications: Clear Aligner and Oral Hygiene Perspectives

IF 2.7 3区医学 Q2 DENTISTRY, ORAL SURGERY & MEDICINE

Orthodontics & Craniofacial Research Pub Date : 2026-08-18 Epub Date: 2026-04-03 DOI:10.1111/ocr.70120

Analia Tahir, Budi Kusnoto, Phimon Atsawasuwan, Grace Viana, Veerasathpurush Allareddy, Tolga F. Tozum, Mohammed H. Elnagar

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引用次数: 0

Abstract

Introduction

The widespread use of smartphones presents a remarkable opportunity for real-time management of orthodontic treatment. The development of orthodontic smartphone applications, such as Dental Monitoring (DM), epitomises the use of Artificial Intelligence Driven Remote Monitoring (AIDRM) for sophisticated image analysis. The primary aim of this study is to evaluate the validity of DM's AI image analysis notification software in detecting unfavorable clinical conditions regarding clear aligner and oral hygiene concerns.

Methods

Twenty-three patients undergoing clear aligner treatment with the implementation of DM were recruited for this study. To assess the validity of DM's AI image analysis software in detecting unfavourable clinical conditions, all notifications were compared to the ‘gold standard’ orthodontist visual exam of uploaded DM scans. A range of 533–1425 observations were assessed for identifying generalised and localised detection of clinical conditions regarding clear aligner and oral hygiene parameters. Then, the accuracy, sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were calculated.

Results

Dental Monitoring AI image analysis software demonstrated a higher accuracy for generalised detection of clear aligner and oral hygiene parameters, while a lower accuracy was demonstrated for localised detection of stated parameters.

Conclusions

Dental monitoring is a viable option for clinical use in remotely monitoring clear aligner and oral hygiene parameters during clear aligner orthodontic treatment. However, the clinician should remain aware that the AI notification software has trouble identifying specific areas of clinical issues, and therefore, the monitoring is not fully automated and must be closely followed by the overseeing orthodontist.

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评估人工智能驱动的监测系统通知：明确对准器和口腔卫生的观点。

智能手机的广泛使用为正畸治疗的实时管理提供了一个非凡的机会。牙齿监测（DM）等正畸智能手机应用程序的发展，体现了人工智能驱动的远程监测（AIDRM）在复杂图像分析中的应用。本研究的主要目的是评估DM的人工智能图像分析通知软件在检测关于清除对准器和口腔卫生问题的不利临床条件方面的有效性。方法：本研究招募了23例接受透明对准器治疗并实施DM的患者。为了评估DM的人工智能图像分析软件在检测不利临床条件方面的有效性，将所有通知与上传的DM扫描的“金标准”正畸医生视觉检查进行比较。评估了533-1425项观察结果，以确定有关清洁对准器和口腔卫生参数的临床状况的普遍和局部检测。然后计算准确性、敏感性、特异性、阳性预测值（PPV）和阴性预测值（NPV）。结果：牙科监测人工智能图像分析软件对清洁对准器和口腔卫生参数的广义检测具有较高的准确性，而对指定参数的局部检测具有较低的准确性。结论：口腔监测是一种可行的选择，可用于临床远程监测清洁矫正器和口腔卫生参数在清洁矫正治疗。然而，临床医生应该意识到，人工智能通知软件在识别临床问题的特定领域方面存在困难，因此，监测不是完全自动化的，必须由监督的正畸医生密切关注。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Orthodontics & Craniofacial Research 医学-牙科与口腔外科

CiteScore

5.30

自引率

3.20%

发文量

审稿时长

>12 weeks

期刊介绍： Orthodontics & Craniofacial Research - Genes, Growth and Development is published to serve its readers as an international forum for the presentation and critical discussion of issues pertinent to the advancement of the specialty of orthodontics and the evidence-based knowledge of craniofacial growth and development. This forum is based on scientifically supported information, but also includes minority and conflicting opinions. The objective of the journal is to facilitate effective communication between the research community and practicing clinicians. Original papers of high scientific quality that report the findings of clinical trials, clinical epidemiology, and novel therapeutic or diagnostic approaches are appropriate submissions. Similarly, we welcome papers in genetics, developmental biology, syndromology, surgery, speech and hearing, and other biomedical disciplines related to clinical orthodontics and normal and abnormal craniofacial growth and development. In addition to original and basic research, the journal publishes concise reviews, case reports of substantial value, invited essays, letters, and announcements. The journal is published quarterly. The review of submitted papers will be coordinated by the editor and members of the editorial board. It is policy to review manuscripts within 3 to 4 weeks of receipt and to publish within 3 to 6 months of acceptance.