Jul 2026· International Journal of Community Medicine and Public Health· Vol 13, pp. 4697-4703· 0 citations· 42 references
TL;DR
AI and DT are transforming pediatric dentistry by improving diagnostic accuracy, patient engagement, preventive care and treatment efficiency, however, their wider adoption requires robust datasets, standardized validation and multicenter clinical studies to ensure safe and effective implementation.
Abstract
The field of pediatric dentistry is undergoing a paradigm shift, moving from a reactive model to one that embraces precision, prevention and the power of Artificial Intelligence (AI) and Digital Technologies (DT). These innovations offer exciting opportunities to transform diagnosis, management and treatment of paediatric oral health conditions. This study evaluates the role of AI and DT in pediatric dentistry, with emphasis on diagnostics, behavioral management, prevention and orthodontic planning. A thorough evaluation of the literature was carried out using Google Scholar, PubMed, Scopus and the Cochrane Library. A comprehensive review was conducted of peer-reviewed publications, clinical trials and meta-analyses published between 2015 and 2026 and included 38 studies. Four areas of evidence were combined: computer-aided orthodontic planning, digital behavioral therapies, smart preventative tracking and automated diagnostics. Deep learning (DL) models, including convolutional neural network (CNN), you only look once version 8 (YOLOv8) and inception residual network version 2 (Inception-ResNet-v2), demonstrated specialist-level accuracy in early caries detection, pathology mapping and cervical vertebral maturation staging. Virtual reality (VR) reduced procedural anxiety, while social robotics improved patient cooperation. Internet of Things (IoT)-enabled smart toothbrushes and machine learning models (ML) supported remote monitoring and personalized prevention; whereas intraoral scanning combined with three-dimensional (3D) printing enabled rapid fabrication of high-precision pediatric dental appliances. AI and DT are transforming pediatric dentistry by improving diagnostic accuracy, patient engagement, preventive care and treatment efficiency. However, their wider adoption requires robust datasets, standardized validation and multicenter clinical studies to ensure safe and effective implementation.
This review synthesizes advances in deep learning and machine learning for oral disease diagnosis, orthodontic treatment prediction, pediatric oral health management, adolescent psychological-oral health interactions, and precision care for special-needs populations, drawing on evidence published predominantly between...
Yuan-Qi Zhang, Tao Wen, Zheng-Rou Wang et al.· International Journal of Art...· 0 citations
Background: Artificial intelligence [AI] has enhanced contemporary dental practice by providing advanced tools for diagnosis, treatment planning, and patient management. Objective: This narrative review examines the current applications of AI in dentistry, evaluates its diagnostic efficacy, identifies challenges for cl...
G. P. Vitor· Research, Society and Develo...· 0 citations
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This review scoped artificial intelligence (AI) in paediatric dentistry to summarize current applications and limitations. A comprehensive literature search was completed across PubMed, Google Scholar, Scopus, Embase, IEEE Xplore, and medRxiv/aArXiv. The preferred Reporting Items for Systematic Reviews and Meta-Analyse...
R. Rokhshad, A. Tichý, Jung-Wei Chen et al.· Australian dental journal· 0 citations
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