人工智能驱动的动态正畸治疗管理:个性化进度跟踪和调整-叙述性回顾。

IF 1.8 Q3 DENTISTRY, ORAL SURGERY & MEDICINE
Frontiers in dental medicine Pub Date : 2025-08-01 eCollection Date: 2025-01-01 DOI:10.3389/fdmed.2025.1612441
Xuanchi Guo, Yuhan Shao
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引用次数: 0

摘要

人工智能(AI)正在通过动态数据驱动策略重新配置正畸治疗范例。本文系统回顾了人工智能在个性化治疗跟踪、实时决策支持、风险预测等方面的多维应用,揭示了其提升临床疗效和患者体验的核心机制。本文将重点介绍人工智能驱动的多模态数据分析(如锥束CT、口腔内扫描和3D面部图像)和深度学习算法(如卷积神经网络)的融合,以阐明牙齿运动轨迹预测和牙根吸收早期检测等关键方面的技术突破。临床实践表明,基于移动医疗平台,通过优化治疗方案制定流程,实现动态调整机制,增强患者依从性,人工智能已经形成了完整的临床应用闭环。目前的研究还需要解决数据隐私保护框架、算法可解释性增强、多中心验证等核心问题。随着跨学科技术的融合和智能正畸系统研发的深入,AI将推动正畸诊疗朝着更加精准、个性化的方向发展,最终实现临床决策模式和患者管理策略的双重创新。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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 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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CiteScore
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