ArticleBMC medical education2025
Exploring dental students' attitudes and perceptions toward artificial intelligence in dentistry in Iran.
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 12 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
12 citing papers in PubMed.
- An exploratory survey of barriers and enablers of AI adoption in rural and urban dental practices in Mecklenburg-Western Pomerania, Germany.Scientific reports · 2026Article
- Medical students' attitudes, usage patterns, and associated factors with DeepSeek adoption in education: a cross-sectional study in China.BMC medical education · 2026Article
- Dentists', dental students' and patients' knowledge, attitudes and practices on artificial intelligence: a scoping review.BMC oral health · 2026Article
- Digital Intelligence in Dental Education: A Bibliometric Analysis.International dental journal · 2026Review
- Preparing future dentists for artificial intelligence: a cross-sectional study of perceptions and educational needs in China.Frontiers in public health · 2026Article
- Artificial intelligence for teaching, training, and assessment in dental education: a domain-based scoping review.Frontiers in medicine · 2026Review
- Exploring Senior Dental Students' Readiness and Perceptions of Artificial Intelligence in Dentistry: Insights From a Cross-Sectional Study.International journal of dentistry · 2026Article
- The Presence and Nature of AI-Use Disclosure Statements in Medical Education Journals: A Bibliometric Study.Perspectives on medical education · 2026Article
- Exploring medical students' attitudes and perceptions toward artificial intelligence in medicine in Shandong Province, China.BMC medical education · 2025Article
- Article
- Artificial Intelligence in Dental Education: A Scoping Review of Applications, Challenges, and Gaps.Dentistry journal · 2025Review
- The current status, knowledge, attitudes, and challenges of generative artificial intelligence use among undergraduate nursing students: a single-center cross-sectional survey of western China.Frontiers in public health · 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
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
introductionAI has the potential to enhance diagnostics, optimize treatment planning, and improve patient care. However, concerns remain regarding professional autonomy, ethical considerations, and the need for adequate training. This research aims to address the gap in understanding how Iranian dental students perceive AI in their future practice. METHODOLOGY: A cross-sectional study was conducted among 235 dental students from different academic years who were selected through stratified sampling. A validated questionnaire with a high Cronbach's alpha coefficient (0.90) was used to assess students' attitudes toward AI. Data were analyzed via descriptive statistics, with a chi-square test examining associations between demographic factors and AI perceptions.
resultsOverall, 80.4% agreed that AI would significantly advance dentistry, particularly in diagnostic applications such as radiographic analysis (75.7%) and periodontal disease detection (78.7%). However, skepticism persisted regarding AI replacing human professionals, with nearly 50% disagreeing that AI could replace dentists and with only 31.1% viewing AI as a definitive diagnostic tool. The attitudes varied by demographic factors, with female students favoring AI inclusion in education and male students exhibiting greater confidence in the diagnostic capabilities of AI. Compared with general dentistry students, specialized students were more confident in AI-assisted implant planning.
conclusionDental students hold a generally positive view of AI's role in dentistry while maintaining caution about its limitations. Integrating AI into dental curricula is essential for addressing knowledge gaps and preparing students for AI-enhanced practice. Future research should balance technological advancements with ethical considerations to ensure that AI effectively contributes to improved dental education and patient care. CLINICAL TRIAL NUMBER: Not applicable.
Indexed as
Identifiers
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.