ArticleCureus2025
Awareness, Perceptions, and Opinions of Artificial Intelligence Among Undergraduate Medical Students at Umm Al-Qura University, Saudi Arabia, in 2025: A Cross-Sectional Study.
Article in Cureus, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers, 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
2 citing papers 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
- Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
BACKGROUND AND
objectiveThe integration of artificial intelligence (AI) education into medical curricula is emphasized by the World Medical Association as AI becomes more prevalent in healthcare, including applications such as image analysis and robotic surgery. This study aimed to assess the awareness, perceptions, and opinions of undergraduate medical students regarding AI and its application in healthcare at Umm Al-Qura University, Makkah, Saudi Arabia. MATERIALS AND
methodsA descriptive cross-sectional study was done in March 2025 at Umm Al-Qura University with 170 undergraduate medical students. A stratified random selection method was used to ensure that each year group was represented correctly. Based on earlier studies, a verified, self-administered online questionnaire was used to collect the data. The tool examined demographic information, knowledge, use, attitudes, and impressions of AI. SPSS Statistics version 20 (IBM Corp., Released 2011. IBM SPSS Statistics for Windows, Version 20.0. Armonk, NY: IBM Corp.) was used to do statistical tests such as chi-square tests, independent t-tests, and one-way ANOVA.
resultsOf the 170 students, 70.0% were female and 91.8% were Saudi nationals. A large majority were aware of AI (95.9%) and ChatGPT (97.1%; OpenAI, San Francisco, CA, USA), with 94.1% having used ChatGPT. Most students (61.2%) viewed AI as a supportive tool for healthcare professionals rather than a replacement. Positive perceptions of AI were associated with higher levels of study (p = 0.006) and AI awareness (p = 0.008), but not with gender, age, or nationality. While many students recognized AI's benefits in diagnosis and decision-making, concerns were expressed regarding dehumanization, job displacement, and ethical risks such as privacy and misinformation. Notably, 55.3% of students reported no formal education on AI, underscoring the need for structured curricular integration.
conclusionsThe study found that Saudi medicine students believed AI was generally beneficial, but they were also cautious. To prepare students for future clinical settings that AI will enhance, it is imperative that formal AI training be included in undergraduate medical education.
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.