Evidence map›Paper›PMID 42039945›Full record

ReviewFrontiers in oral health2026

Artificial intelligence and immersive digital technologies in periodontal education: a systematic review.

Yiping Wei, Ying Li, Wenjie Hu, Jun Kang, Ziyao Han, Min Zhen, Cui Wang

Abstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in Frontiers in oral health, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed, 1 pooled it
–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 synthesis or guideline pooled it.

  1. Pooled it
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

7 authors.

Yiping WeiDepartment of Periodontology, National Center for Stomatology, National Clinical Research Center for Oral Diseases, National Engineering Research Center of Oral Biomaterials and Digital Medical Devices, Peking University School and Hospital of Stomatology, Beijing, China.
Ying LiDepartment of Periodontology, National Center for Stomatology, National Clinical Research Center for Oral Diseases, National Engineering Research Center of Oral Biomaterials and Digital Medical Devices, Peking University School and Hospital of Stomatology, Beijing, China.
Wenjie HuDepartment of Periodontology, National Center for Stomatology, National Clinical Research Center for Oral Diseases, National Engineering Research Center of Oral Biomaterials and Digital Medical Devices, Peking University School and Hospital of Stomatology, Beijing, China.
Jun KangDepartment of Periodontology, National Center for Stomatology, National Clinical Research Center for Oral Diseases, National Engineering Research Center of Oral Biomaterials and Digital Medical Devices, Peking University School and Hospital of Stomatology, Beijing, China.
Ziyao HanDepartment of Periodontology, National Center for Stomatology, National Clinical Research Center for Oral Diseases, National Engineering Research Center of Oral Biomaterials and Digital Medical Devices, Peking University School and Hospital of Stomatology, Beijing, China.
Min ZhenDepartment of Periodontology, National Center for Stomatology, National Clinical Research Center for Oral Diseases, National Engineering Research Center of Oral Biomaterials and Digital Medical Devices, Peking University School and Hospital of Stomatology, Beijing, China.
Cui WangDepartment of Periodontology, National Center for Stomatology, National Clinical Research Center for Oral Diseases, National Engineering Research Center of Oral Biomaterials and Digital Medical Devices, Peking University School and Hospital of Stomatology, Beijing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objectives: The purpose of the systematic review was to evaluate the application and efficacy of artificial intelligence (AI) and immersive digital technologies in periodontal education. Methods: We conducted a comprehensive search of PubMed, Embase, Web of Science, and Cochrane Central Register of Controlled Trials up to July 2025, supplemented by manual searches. Risk of bias was assessed using the Cochrane Risk of Bias 2.0 tool for randomized controlled trials and the Joanna Briggs Institute checklists for quasi-experimental and analytical cross-sectional studies. Results: Fifteen studies encompassing 3062 dental trainees and practitioners were included. Immersive digital technologies, including haptics-based virtual reality (VR), 360°VR, and virtual patient simulations, improved procedural skills, learner engagement, and communication abilities, particularly when combined with traditional training. AI applications such as explainable AI, AI-enhanced imaging, and large language models (LLMs) showed mixed outcomes. AI-assisted diagnostic tools offered limited advantage over conventional methods and may introduce automation bias. LLMs displayed variable accuracy and reliability. Conclusions: Dental educators should use blended, sequenced immersive digital technologies to enhance procedural and communication skills. AI diagnostic tools require safeguards against automation bias. LLMs can assist with grading but are unreliable as test-takers. Future multi-center randomized controlled trials are needed to assess long-term effectiveness and cost-efficiency. Systematic Review Registration: https://www.crd.york.ac.uk/PROSPERO/view/CRD420251027251, PROSPERO CRD420251027251.

Indexed as

artificial intelligencedental educationdigital learningimmersive technologiesperiodontics

Identifiers

PMID42039945
PMCPMC13103527

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.