Evidence map›Paper›PMID 42081692›Full record

SynthesisEuropean journal of dental education : official journal of the Association for Dental Education in Europe2026

Artificial Intelligence (AI) Impact on Dental Education and Curriculum: A Systematic Review Following PRISMA Guidelines.

Laura Reyes-Alardo, Franklin García-Godoy, Romina Paola Quiroga, María Isabel Pardo Silva, Rita Licelot Cruz, Darwin Munoz, Massiel Cohen Camacho, Luis Ney Quiterio Montero

Abstract readSystematic Review
In one paragraph

Synthesis in European journal of dental education : official journal of the Association for Dental Education in Europe, 2026. 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

8 authors.

Laura Reyes-AlardoUniversidad Federico Henríquez y Carvajal (UFHEC), Santo Domingo, Dominican Republic.ORCID https://orcid.org/0000-0003-4989-8707
Franklin García-GodoyUniversity of Tennessee Health Science Center, College of Dentistry, Memphis, TN, USA.ORCID https://orcid.org/0000-0001-8133-3306
Romina Paola QuirogaUniversity of Toronto, Faculty of Dentistry, Toronto, Canada.ORCID https://orcid.org/0009-0004-6967-3446
María Isabel Pardo SilvaUniversidad El Bosque, Bogotá, Colombia.ORCID https://orcid.org/0000-0002-5239-6567
Rita Licelot CruzUniversidad Federico Henríquez y Carvajal (UFHEC), Santo Domingo, Dominican Republic.ORCID https://orcid.org/0000-0002-5653-3776
Darwin MunozUniversidad Federico Henríquez y Carvajal (UFHEC), Santo Domingo, Dominican Republic.ORCID https://orcid.org/0000-0003-4691-2614
Massiel Cohen CamachoUniversidad APEC (UNAPEC), Santo Domingo, Dominican Republic.ORCID https://orcid.org/0009-0003-3791-982X
Luis Ney Quiterio MonteroUniversity of Toronto, Faculty of Dentistry, Toronto, Canada.ORCID https://orcid.org/0000-0003-1421-0490

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

importanceAI technologies increasingly influence dental education, but their instructional value, stakeholder perspectives, and institutional implications require further study.

objectiveTo synthesise evidence on AI's impact in undergraduate dental education, focusing on learning outcomes, stakeholder perspectives, and curriculum design. EVIDENCE REVIEW: Following PRISMA 2020 guidelines, researchers searched PubMed, Scopus, Web of Science, IEEE Xplore, and Google Scholar for articles published between January 2015 and February 2025. Eligibility followed an adapted PECO framework: undergraduate dental students or faculty (Population); AI use in teaching, clinical training, or administration (Exposure); conventional or non-AI digital methods (Comparator); and outcomes including knowledge retention, skills, critical thinking, stakeholder perspectives, and curriculum effectiveness (Outcome). The initial pool of 402 references underwent systematic screening, quality appraisal, and AI-focused refinement across four stages, resulting in a final dataset of 107 studies meeting a minimum quality threshold (≥ 3) using validated appraisal tools.

findingsAI-powered educational resources, including adaptive learning platforms, intelligent tutoring systems, and generative AI tools, improved knowledge retention, technical skills, and clinical decision-making. Students benefited from personalised feedback, adaptive instruction, and increased engagement. Faculty expressed cautious optimism, tempered by gaps in training, technical readiness, and ethical guidance. Adoption patterns were shaped by generational, cultural, and infrastructural factors.

conclusionsAI enhances cognitive, technical, and clinical learning while complementing traditional instruction. Successful integration requires structured faculty development, clear ethical frameworks, institutional support, and close collaboration among educators, researchers, and technologists to ensure AI supports, rather than replaces, core clinical training and professional decision-making. Coordinated strategies addressing pedagogy, technical competence, and ethics will maximise AI's educational impact and support sustainable curriculum transformation in dental education.

Indexed as

Artificial IntelligenceCurriculumEducation, DentalHumansartificial intelligenceclinical trainingcurriculum integrationdental educationknowledge retentiontechnical skills

Identifiers

PMID42081692
PMCPMC13686658

What OpenQuestion holds

Textmetadata
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.