Evidence map›Paper›PMID 42437241›Full record

ArticleCureus2026

Readiness and Knowledge of Medical Students and Staff in the UAE Toward the Integration of Artificial Intelligence in Medicine.

Dima Al-Qaimari, Aya Ewida, Omar Abu Eid, Hisham Sinan, Ola Yasir Abdelaziz Osman, Reem Ibrahim Ali Mohamad, Emad A Nosair, Amal Hussein

Abstract read
In one paragraph

Article in Cureus, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

8 authors.

Dima Al-QaimariClinical Sciences, College of Medicine, University of Sharjah, Sharjah, ARE.
Aya EwidaClinical Sciences, College of Medicine, University of Sharjah, Sharjah, ARE.
Omar Abu EidClinical Sciences, College of Medicine, University of Sharjah, Sharjah, ARE.
Hisham SinanClinical Sciences, College of Medicine, University of Sharjah, Sharjah, ARE.
Ola Yasir Abdelaziz OsmanClinical Sciences, College of Medicine, University of Sharjah, Sharjah, ARE.
Reem Ibrahim Ali MohamadClinical Sciences, College of Medicine, University of Sharjah, Sharjah, ARE.
Emad A NosairBasic Medical Sciences, College of Medicine, University of Sharjah, Sharjah, ARE.
Amal HusseinFamily and Community Medicine and Behavioral Sciences, University of Sharjah, Sharjah, ARE.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background and aim Artificial intelligence (AI) has become an indispensable component of medical practice. Studies have shown that medical students worldwide are often ill-prepared to take full advantage of these technologies in their future practice due to inadequate training and a shortage of qualified instructors. These factors hinder the adoption of AI-focused curricula; therefore, this study aims to explore medical students' and faculty's knowledge and attitudes toward AI applications in the medical field, as well as their readiness for its integration into the medical curriculum, highlighting both the benefits and barriers. Methods A cross-sectional study was conducted on medical students (years 1-5) and faculty members from the University of Sharjah College of Medicine (UOSCOM), Sharjah, UAE. They were recruited via convenience sampling between February and March 2023. Students and faculty completed self-administered questionnaires, both online and in person. Analysis was performed using IBM SPSS Statistics for Windows, Version 26 (Released 2018; IBM Corp., Armonk, NY, USA). Results Of a total of 413 participants, 74.3% (faculty and students) agreed that the medical field has benefited from AI. Interestingly, 54.3% of students agreed on implementing AI in the curriculum, and 79.3% believe it is necessary, as they see it as a way to empower their careers in the future. However, 51.9% expressed concerns regarding the increase in workload. Of the 45 faculty participants, 66.7% believe that teaching AI would be an addition to their CVs, while 40% disagree that adding the course will increase their workload. Moreover, 77.8% are willing to participate in the course. Conclusions and recommendations The findings revealed a general positive perception, with both groups acknowledging the benefits of AI in medicine. Students show awareness of AI applications in education and healthcare, while faculty express willingness to teach AI courses for professional development. However, we recommend that future studies assess students' baseline computer knowledge and correlate faculty members' specialty fields with their willingness to teach.

Indexed as

artificial intelligencehealth informaticsmedical educationmedical facultymedical students

Identifiers

PMID42437241
PMCPMC13355148

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.