Evidence map›Paper›PMID 41372904›Full record

ArticleBMC medical education2025

Application and development of artificial intelligence and immersive technologies in dental education: a scoping review.

Shuheng Huang, Yang Qu, Yutong Sun, Sishi Chen, Lisha Gu

Abstract readScoping Review
In one paragraph

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 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Shuheng Huang *Hospital of Stomatology, Guanghua School of Stomatology, Sun Yat-sen University, Guangzhou, China.
Yang Qu *Hospital of Stomatology, Guanghua School of Stomatology, Sun Yat-sen University, Guangzhou, China.
Yutong SunHospital of Stomatology, Guanghua School of Stomatology, Sun Yat-sen University, Guangzhou, China.
Sishi ChenHospital of Stomatology, Guanghua School of Stomatology, Sun Yat-sen University, Guangzhou, China.
Lisha GuHospital of Stomatology, Guanghua School of Stomatology, Sun Yat-sen University, Guangzhou, China. gulisha@mail.sysu.edu.cn.

Funding

Natural Science Foundation of Guangdong Province 2025A1515010997
6 · The paper itself

Abstract

backgroundArtificial intelligence (AI) has been developing rapidly recently, with large language models such as Chat Generative Pre-trained Transformer (ChatGPT) garnering widespread attention across various fields globally. This scoping review examines the applications and advancements of AI, including natural language processing and computer simulation, as well as immersive technologies such as virtual reality (VR), augmented reality (AR), and mixed reality (MR) in dental education. Despite substantial research highlighting the benefits of AI in specific dental disciplines, a comprehensive review of the latest developments in AI within dental education has yet to be conducted.

methodsA scoping review methodology was employed to identify relevant articles published between 2022 and 2024. Five databases were used to identify studies that utilized AI, VR, AR, and MR within dental education: Web of Science, Embase, PubMed, Scopus, and the Educational Resources Information Center (ERIC). The search strategy adhered to the guidelines set forth by the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews (PRISMA-ScR). Research was classified by digital technology type and its implementation across dental specialties.

resultsOf the 1401 initial articles identified, 928 full-text articles were screened, and 76 ultimately met the selection criteria for the review. The selected research focused on AI, VR, AR, or MR applications within dental education.

conclusionThis review underscores the transformative impact of AI and immersive technologies on dental education. By deepening our understanding and expanding the application of these technologies, we can improve educational outcomes through better cognitive visualization, standardized clinical training, and integrated multidisciplinary learning. Future research should focus on optimizing AI integration strategies and developing best practices to leverage these advanced technologies in dental education fully.

Indexed as

Artificial IntelligenceEducation, DentalVirtual RealityAugmented RealityComputer SimulationGenerative Artificial IntelligenceHumansNatural Language ProcessingArtificial intelligenceAugmented realityDental educationImmersive technologiesMixed realityVirtual reality

Identifiers

PMID41372904
PMCPMC12801878

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

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.