AI-driven dynamic orthodontic treatment management: personalized progress tracking and adjustments—a narrative review

Artificial intelligence (AI) is reconfiguring the orthodontic treatment paradigm through dynamic data-driven strategies. In this paper, we systematically review the multidimensional applications of AI in personalized treatment tracking, real-time decision support, and risk prediction, and reveal its...

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Main Authors: Xuanchi Guo, Yuhan Shao
Format: Article
Language:English
Published: Frontiers Media S.A. 2025-08-01
Series:Frontiers in Dental Medicine
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Online Access:https://www.frontiersin.org/articles/10.3389/fdmed.2025.1612441/full
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author Xuanchi Guo
Yuhan Shao
author_facet Xuanchi Guo
Yuhan Shao
author_sort Xuanchi Guo
collection DOAJ
description Artificial intelligence (AI) is reconfiguring the orthodontic treatment paradigm through dynamic data-driven strategies. In this paper, we systematically review the multidimensional applications of AI in personalized treatment tracking, real-time decision support, and risk prediction, and reveal its core mechanisms to enhance clinical efficacy and patient experience. This review will focus on the fusion of AI-driven multimodal data analysis (e.g., cone-beam CT, intraoral scanning, and 3D facial images) and deep learning algorithms (e.g., convolutional neural networks) to elucidate the technological breakthroughs in key aspects such as tooth movement trajectory prediction and early detection of root resorption. Clinical practice has shown that AI has formed a complete closed loop of clinical application by optimizing the process of treatment plan development, realizing dynamic adjustment mechanisms, and enhancing patient compliance based on mobile medical platforms. Current research still needs to address core issues such as data privacy protection framework, algorithm interpretability enhancement, and multi-center validation. With the integration of interdisciplinary technology and the deepening of the research and development of intelligent orthodontic systems, AI will promote orthodontic diagnosis and treatment in the direction of more accuracy and personalization and ultimately realize the dual innovation of clinical decision-making mode and patient management strategy.
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spelling doaj-art-8bc5a96e63e048749789ee2f425ae0a92025-08-20T03:58:11ZengFrontiers Media S.A.Frontiers in Dental Medicine2673-49152025-08-01610.3389/fdmed.2025.16124411612441AI-driven dynamic orthodontic treatment management: personalized progress tracking and adjustments—a narrative reviewXuanchi Guo0Yuhan Shao1Department of Dental Medicine, Shandong University, Jinan, Shandong, ChinaState Key Laboratory of Oral Diseases & National Center for Stomatology & National Clinical Research Center for Oral Diseases, West China Hospital of Stomatology, Sichuan University, Chengdu, ChinaArtificial intelligence (AI) is reconfiguring the orthodontic treatment paradigm through dynamic data-driven strategies. In this paper, we systematically review the multidimensional applications of AI in personalized treatment tracking, real-time decision support, and risk prediction, and reveal its core mechanisms to enhance clinical efficacy and patient experience. This review will focus on the fusion of AI-driven multimodal data analysis (e.g., cone-beam CT, intraoral scanning, and 3D facial images) and deep learning algorithms (e.g., convolutional neural networks) to elucidate the technological breakthroughs in key aspects such as tooth movement trajectory prediction and early detection of root resorption. Clinical practice has shown that AI has formed a complete closed loop of clinical application by optimizing the process of treatment plan development, realizing dynamic adjustment mechanisms, and enhancing patient compliance based on mobile medical platforms. Current research still needs to address core issues such as data privacy protection framework, algorithm interpretability enhancement, and multi-center validation. With the integration of interdisciplinary technology and the deepening of the research and development of intelligent orthodontic systems, AI will promote orthodontic diagnosis and treatment in the direction of more accuracy and personalization and ultimately realize the dual innovation of clinical decision-making mode and patient management strategy.https://www.frontiersin.org/articles/10.3389/fdmed.2025.1612441/fullorthodonticsdigital treatment simulationartificial intelligenceconvolutional neural networkspatient engagement
spellingShingle Xuanchi Guo
Yuhan Shao
AI-driven dynamic orthodontic treatment management: personalized progress tracking and adjustments—a narrative review
Frontiers in Dental Medicine
orthodontics
digital treatment simulation
artificial intelligence
convolutional neural networks
patient engagement
title AI-driven dynamic orthodontic treatment management: personalized progress tracking and adjustments—a narrative review
title_full AI-driven dynamic orthodontic treatment management: personalized progress tracking and adjustments—a narrative review
title_fullStr AI-driven dynamic orthodontic treatment management: personalized progress tracking and adjustments—a narrative review
title_full_unstemmed AI-driven dynamic orthodontic treatment management: personalized progress tracking and adjustments—a narrative review
title_short AI-driven dynamic orthodontic treatment management: personalized progress tracking and adjustments—a narrative review
title_sort ai driven dynamic orthodontic treatment management personalized progress tracking and adjustments a narrative review
topic orthodontics
digital treatment simulation
artificial intelligence
convolutional neural networks
patient engagement
url https://www.frontiersin.org/articles/10.3389/fdmed.2025.1612441/full
work_keys_str_mv AT xuanchiguo aidrivendynamicorthodontictreatmentmanagementpersonalizedprogresstrackingandadjustmentsanarrativereview
AT yuhanshao aidrivendynamicorthodontictreatmentmanagementpersonalizedprogresstrackingandadjustmentsanarrativereview