ArticleFrontiers in medicine2026
Perception of integrating an AI teaching module into medical education curriculum.
Article in Frontiers in medicine, 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.
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
1 citing paper in PubMed, 1 synthesis or guideline pooled it.
- Medical Students' Attitudes, Perceptions, and Self-Reported Familiarity With AI in Health Care: Systematic Review and Meta-Analysis.JMIR medical education · 2026Pooled it
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background and aims: Artificial intelligence (AI) is evolving into a revolutionary tool as medical education rapidly adapts to meet the demands of modern healthcare. This study examined the perceptions of faculty members, teaching assistants, and medical students regarding the integration of AI teaching modules into the undergraduate medical curriculum at Alfaisal University in Riyadh, Saudi Arabia. Methods: A cross-sectional questionnaire-based survey was conducted among 201 participants (68 faculty members, 16 teaching assistants, and 117 medical students). The survey collected demographic data (age, gender, nationality, academic role, and faculty rank or student year of study) and explored perceived advantages (e.g., innovation, efficiency, accuracy), disadvantages (e.g., workload, resistance, job replacement, overreliance on technology), and views on the appropriate stage for introducing AI in the curriculum. Responses were measured on a five-point Likert scale and analyzed using descriptive and inferential statistics. Results: The majority of respondents expressed favorable perceptions of AI integration, highlighting its potential to inspire innovation, improve efficiency, enhance clinical precision, and broaden medical specialties. Over half (55.7%) recommended introducing AI during preclinical years, while 32.8% preferred the clinical years. Conclusion: The findings demonstrate strong support for the early integration of AI into Alfaisal University's medical curriculum. These insights provide evidence to guide curriculum development and prepare future medical professionals for AI-driven practice.
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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.