ArticleBMC medical education2025
Educational aspects of artificial intelligence in oral and maxillofacial radiology: insights from a scoping review.
Article in BMC medical education, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 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
2 citing papers in PubMed.
- Influence of Oral and Maxillofacial Radiology Training and Experience on Attitudes Toward Artificial Intelligence in Dentistry: A Cross-Sectional Questionnaire Study.Healthcare (Basel, Switzerland) · 2026Article
- Educational aspects of artificial intelligence in oral and maxillofacial radiology: insights from a scoping review.BMC medical education · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectiveTo gather evidence from literature on Artificial Intelligence applications in educational settings and assess the educational elements involved in Oral and Maxillofacial Radiology.
methodsA systematic scoping review was performed using predefined keywords and truncation search strategies across PubMed, Scopus, and Web of Science, focusing on artificial intelligence, oral and maxillofacial radiology, and dental education.
resultsThe initial search retrieved 3,124 articles published from 2014 to November 2024 were screened. Of these, only 8 articles met the criteria, specifically focusing on educational aspects within Oral and Maxillofacial Radiology; the others were excluded mainly because they focused on general dentistry. Three studies focus on Knowledge, Attitude, and Perception of dental students and educators, while others involve clinical applications among students, Generative Adversarial Networks for radiographic image generation, and large language models (LLMs) for theoretical OMFR comparison among students and LLMs. The educational elements identified include utilizing AI as a learning tool, incorporating AI knowledge and fundamentals into lectures, and evaluating AI’s performance in theoretical and clinical OMFR.
conclusionsProspective research on the educational aspects of Artificial Intelligence (AI) integration in Oral and Maxillofacial Radiology appears promising, given the current limited evidence base, which tends to emphasize clinical implications more than direct educational value. Additionally, strategically incorporating AI into pedagogical frameworks can help develop dental professionals with improved technological literacy, a strong understanding, and greater confidence in using AI technologies.
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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.