ReviewWorld journal of methodology2025
Artificial intelligence in revolutionizing orthodontic practice.
Review in World journal of methodology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
3 citing papers in PubMed.
- YOLO11-guided swin transformer for molar occlusion classification.Scientific reports · 2026Article
- Machine learning algorithms for predicting quality of life improvements after digital orthodontic treatment: a retrospective analysis.Biomedical engineering online · 2026Article
- Novel desktop robotic system for orthodontic archwire bending: an accuracy and efficiency comparison with manual bending.American journal of translational research · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
This analytical research paper explores the transformative impact of artificial intelligence (AI) in orthodontics, with a focus on its objectives: Identifying current applications, evaluating benefits, addressing challenges, and projecting future developments. AI, a subset of computer science designed to simulate human intelligence, has seen rapid integration into orthodontic practice. The paper examines AI technologies such as machine learning, deep learning, natural language processing, computer vision, and robotics, which are increasingly used to analyze patient data, assist with diagnosis and treatment planning, automate routine tasks, and improve patient communication. AI systems offer precise malocclusion diagnoses, predict treatment outcomes, and customize treatment plans by leveraging dental imagery. They also streamline image analysis, improve diagnostic accuracy, and enhance patient engagement through personalized communication. The objectives include evaluating the benefits of AI in terms of efficiency, accuracy, and personalized care, while acknowledging the challenges like data quality, algorithm transparency, and practical implementation. Despite these hurdles, AI presents promising prospects in advanced imaging, predictive analytics, and clinical decision-making. In conclusion, AI holds the potential to revolutionize orthodontic practices by improving operational efficiency, diagnostic precision and patient outcomes. With collaborative efforts to overcome challenges, AI could play a pivotal role in advancing orthodontic care.
Indexed as
Identifiers
What OpenQuestion holds
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.