ArticleProgress in orthodontics2021
Applications of artificial intelligence and machine learning in orthodontics: a scoping review.
Article in Progress in orthodontics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT05348109 (Assessment of Decision Support System Software in Extraction and Anchorage Planning Among Adult Patients Using Computer Algorithm), which is not on this map. Cited by 85 papers, 5 of them syntheses that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Assessment of Decision Support System Software in Extraction and Anchorage Planning Among Adult Patients Using Computer Algorithm
Who cites it
85 citing papers in PubMed, 5 syntheses or guidelines pooled it.
- Artificial intelligence for craniofacial and mandibular growth prediction: A systematic review.Clinical oral investigations · 2026Pooled it
- AI in orthodontic treatment planning: a systematic review comparing learning approaches.BMC oral health · 2026Pooled it
- Parameter-level comparison of artificial intelligence and manual cephalometric measurements: a systematic review and meta-analysis.Frontiers in dental medicine · 2026Pooled it
- Artificial Intelligence for Detecting Cephalometric Landmarks: A Systematic Review and Meta-analysis.Journal of digital imaging · 2023Pooled it
- Accuracy of automated 3D cephalometric landmarks by deep learning algorithms: systematic review and meta-analysis.La Radiologia medica · 2023Pooled it
- Clinical audit of an artificial intelligence (AI) empowered smile simulation system: a prospective clinical trial.Scientific reports · 2024Trial
- Artificial intelligence in orthodontics: clinical maturity, evidence gaps, and emerging applications-a narrative review.The Saudi dental journal · 2026Review
- Algorithmovigilance in AI-Based Oral-Health Surveillance: Temporal Drift, Cross-Survey Differences, and Predictor-Level Structural Stability in Population-Level Severe Tooth Loss Prediction.Diagnostics (Basel, Switzerland) · 2026Article
- Comparison of automated algorithm-based versus manual dental landmark placement for model analysis and evaluation of orthodontic quality indices.European journal of orthodontics · 2026Article
- Charting the artificial intelligence revolution in orthodontics : A bibliometric analysis of key players, collaborations, and research directions.Journal of orofacial orthopedics = Fortschritte der Kieferorthopadie : Organ/official journal Deutsche Gesellschaft fur Kieferorthopadie · 2026Review
- Soft Tissue Cephalometric Analysis of the Lips in Orthodontic Diagnosis and Treatment Planning: A Narrative Review.Cureus · 2026Review
- Benchmarking GPT-5, Gemini 2.5 Pro, Grok 4, and other LLMs on pediatric dentistry questions from a dental specialization exam.Scientific reports · 2026Article
- Review
- Prediction of unerupted canines and premolars widths in an Emirati population: development and validation of regression and machine learning models.Scientific reports · 2026Article
- Multilevel Determinants of Engagement in Lifelong Learning in Orthodontics From Formal to AI-Supported Approaches: Development of a Conceptual Framework Through a Qualitative Study.JMIR medical education · 2026Article
- Teeth identification and numbering in mixed dentition: evaluating deep learning models for pediatric panoramic radiographs.BMC oral health · 2026Article
- Machine learning algorithms for predicting quality of life improvements after digital orthodontic treatment: a retrospective analysis.Biomedical engineering online · 2026Article
- Performance Validation of ORTHOSEG, a Novel Artificial Intelligence Tool for the Segmentation of Orthopantomographs and Intra-Oral X-Rays.Clinics and practice · 2026Article
- Current Applications and Future Perspectives of Artificial Intelligence in Face-Driven Orthodontics: A Scoping Review.Biomimetics (Basel, Switzerland) · 2026Review
- Assessment of AI-based cephalometric landmark recognition on lateral cephalometric radiographs.Frontiers in oral health · 2026Article
25 more citing papers are in PubMed but not listed here.
Corrections and comments
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
introductionThis scoping review aims to provide an overview of the existing evidence on the use of artificial intelligence (AI) and machine learning (ML) in orthodontics, its translation into clinical practice, and what limitations do exist that have precluded their envisioned application.
methodsA scoping review of the literature was carried out following the PRISMA-ScR guidelines. PubMed was searched until July 2020.
resultsSixty-two articles fulfilled the inclusion criteria. A total of 43 out of the 62 studies (69.35%) were published this last decade. The majority of these studies were from the USA (11), followed by South Korea (9) and China (7). The number of studies published in non-orthodontic journals (36) was more extensive than in orthodontic journals (26). Artificial Neural Networks (ANNs) were found to be the most commonly utilized AI/ML algorithm (13 studies), followed by Convolutional Neural Networks (CNNs), Support Vector Machine (SVM) (9 studies each), and regression (8 studies). The most commonly studied domains were diagnosis and treatment planning-either broad-based or specific (33), automated anatomic landmark detection and/or analyses (19), assessment of growth and development (4), and evaluation of treatment outcomes (2). The different characteristics and distribution of these studies have been displayed and elucidated upon therein.
conclusionThis scoping review suggests that there has been an exponential increase in the number of studies involving various orthodontic applications of AI and ML. The most commonly studied domains were diagnosis and treatment planning, automated anatomic landmark detection and/or analyses, and growth and development assessment.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.