ReviewBMC medical education2026
Generative Artificial Intelligence-driven orthodontic education practices.
Review in BMC medical education, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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
1 citing paper in PubMed.
- Beyond the typodont: deliberate practice, experiential learning, and feedback in postgraduate orthodontic education.Frontiers in medicine · 2026Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors.
Funding
Abstract
Generative Artificial Intelligence (GenAI) is transforming medical education, including in the field of orthodontics. This paper presents an overview of prominent GenAI models and orthodontic platforms, such as ChatGPT, DeepSeek, GANs, and Diffusion Models, CephGPT-4, iOrthoPredictor, offer a wide range of capabilities, from knowledge-based Q&A and clinical diagnostics to image generation and treatment simulation. The integration of GenAI with established teaching strategies and learning theories were also introduced, with exmples exploring GenAI applications across four key domains of orthodontic education: knowledge dissemination, clinical practice, teaching outcome assessment, and medical research. GenAI demonstrates capabilities in generating personalized educational content, optimizing curriculum design, and enhancing learning efficiency, and facilitates case simulation, diagnostic assistance, and virtual training modules, thereby supporting the development of practical clinical skills. The technology further contributes to education through personalized performance assessments and feedback mechanisms that improve learning outcomes. In research area, GenAI aids in literature retrieval, data analysis, and academic writing. Despite these promising applications, limitations such as inaccurate information, ethical challenges, excessive dependence, academic misconduct and educational integrity also exist. Proposed solutions involve the integration of GenAI with validated medical resources, implementation of robust data security protocols, and the establishment of guidelines for responsible utilization in educational settings. While GenAI offers significant potential to advance orthodontic education, its effective and ethical implementation requires careful navigation of these limitations and challenges. The development of appropriate safeguards and best practice guidelines will be essential to maximize benefits while mitigating risks associated with this emerging technology.
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.