ArticleBMC medical education2025
Medical undergraduate students' awareness and perspectives on artificial intelligence: A developing nation's context.
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 5 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
5 citing papers in PubMed.
- Use, Concerns, and Perspectives on AI in Health Care Among French Health Professionals and Students: Web-Based Cross-Sectional Survey.JMIR medical education · 2026Article
- Stakeholder Perspectives of Implementation Barriers of Artificial Intelligence in Eye Care: A qualitative framework-based study.Ophthalmic & physiological optics : the journal of the British College of Ophthalmic Opticians (Optometrists) · 2026Article
- Medical students perceptions and attitudes toward the use of generative artificial intelligence in clinical decision-making: a nationwide cross-sectional survey in China.BMC medical education · 2026Article
- Generative AI in perioperative medicine and anesthesiology: ethical integration, educational innovation, and the future of clinical professionalism.Journal of anesthesia · 2026Review
- Physician perceptions of artificial intelligence in Northern Italy healthcare: a survey of fears and expectations.Frontiers in artificial intelligence · 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
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundArtificial intelligence (AI) is reshaping healthcare, yet its integration into medical education remains limited. This study assesses undergraduate healthcare students' knowledge and perceptions of AI, its applications, challenges, and the need for AI education in healthcare curricula.
methodsA cross-sectional study was conducted at Riphah International University from August to October 2023, involving 939 undergraduate students from medical, dental, pharmacy, nursing, and physical therapy disciplines. Data was collected using a validated questionnaire and analyzed using IBM SPSS Version 26. Inferential statistical test such as The Kruskal-Wallis H and Mann-Whitney U tests were applied to compare AI knowledge and perceptions across disciplines and genders.
resultsResults demonstrated moderate AI knowledge, with significant differences across disciplines (p = 0.039). BDS students had the highest AI knowledge, while nursing students scored the lowest. Most students (77%) attended AI-related talks, but only 11.8% had formal AI training. Perceptions toward AI's role in patient care were generally positive, with 73.6% believing AI could aid in patient documentation and 68.7% supporting its role in selecting health interventions. Concerns were raised about AI's impact on job displacement, ethical challenges, and feasibility in developing countries. Despite this, 78.8% supported AI integration into medical curricula, and 82.2% endorsed AI training as part of medical education.
conclusionUndergraduate healthcare students recognize AI's potential in medicine but express concerns about ethical implications and job displacement. The findings highlight the need for structured AI education in medical curricula to bridge knowledge gaps and prepare future healthcare professionals for AI-driven practice.
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.