Evidence map›Paper›PMID 40575224›Full record

ReviewCureus2025

Shaping the Future of Dental Education: A Scoping Review of Artificial Intelligence (AI) Integration Strategies.

Fawziah Ahmed A Alzahrani, Lubna Alolaiwi, Sulaiman A Alshammari

Abstract readReview
In one paragraph

Review in Cureus, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
  4. Review
  5. 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

3 authors.

Fawziah Ahmed A AlzahraniDepartment of Dental Public Health, College of Medicine and Dentistry, Riyadh Elm University, Riyadh, SAU.
Lubna AlolaiwiDepartment of Dentistry, Riyadh Elm University, Riyadh, SAU.
Sulaiman A AlshammariDepartment of Family and Community Medicine, College of Medicine, King Saud University, Riyadh, SAU.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Dental education is one of the fields that have been impacted by artificial intelligence (AI), with new trends such as adaptive learning, virtual simulation, and better diagnostic tools. Despite the many opportunities to use AI in curricula and clinical settings, AI integration has its limitations, highlighted by concerns and challenges such as ethical issues, current and future legal frameworks, and heterogeneity in the preparedness of educators and learners. This study presents a scoping critique of the AI initiatives in dental education and training, as well as analyses of its possibilities, effects, issues, and trends that may inform practice- and research-based curricular improvement and AI preparedness. The current research is based on data obtained from 15 studies included in the scoping review, comprising systematic reviews, observational studies, cross-sectional surveys, and literature reviews, all published in English between January 2020 and January 2024. Basic information was garnered on the features of the studies, the AI technologies and applications, the objects and samples, the results, and the limitations. Thematic synthesis identified four primary areas of focus: curriculum integration, diagnosing and clinical objectives, educators' and students' preparedness, and ethical and legislation concerns. The review also emphasizes how AI can revolutionize dental education by making learning individualized, diagnosis better, and providing new instruments in teaching. Specific conclusions focus on the recent curriculum necessity in schools, increased preparedness of educators and students, and ethical considerations of bias and data protection. However, there is still very low awareness and training among the employees, which does not support readiness. Ethical and regulatory issues are still among the most important obstacles. This paper therefore argues that only when these gaps are addressed can AI be fully integrated and begin to revolutionize dental education and practice. AI is believed to have great benefits for dentistry education and practice. To fully realize its potential, it must offer educators and students attention to some of the gaps they may not be fully prepared for, devise a set of ethical rules, and establish effective regulatory norms. The results suggest that large-scale, multicenter studies must be conducted to replicate results and explore the full potential of AI integration. This review goes beyond listing AI tools by critically assessing their effectiveness in curriculum design, diagnostic accuracy, and institutional readiness. It synthesizes thematic findings to guide future implementation and policy frameworks in dental education.

Indexed as

artificial intelligencecurriculum integrationdental educationdiagnostic toolseducator readinessethical challengespersonalized learningregulatory frameworks

Identifiers

PMID40575224
PMCPMC12202060

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.