Observational studySaudi medical journal2022
Artificial intelligence in radiology: Are Saudi residents ready, prepared, and knowledgeable?
Observational study in Saudi medical journal, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers, 2 of them syntheses that pooled it.
What it found
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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.
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Who cites it
18 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Healthcare professionals' perspectives on artificial intelligence in patient care: a systematic review of hindering and facilitating factors on different levels.BMC health services research · 2025Pooled it
- The current state, challenges, and future directions of artificial intelligence in healthcare in Saudi Arabia: systematic review.Frontiers in artificial intelligence · 2025Pooled it
- Artificial Intelligence Integration in Radiology in Saudi Arabia: A Cross-Sectional Survey of Workforce Readiness and Implementation Challenges.Healthcare (Basel, Switzerland) · 2026Article
- Radiology Staff Experiences With Integrating Artificial Intelligence Into Radiology Practice in a Swedish Hospital: Qualitative Case Study.JMIR formative research · 2025Article
- Perception and Understanding of Artificial Intelligence Among Gastroenterology Fellows and Early Career Gastroenterologists: A Nationwide Cross-Sectional Survey Study.Digestive diseases and sciences · 2025Article
- Integration of artificial intelligence in radiology education: a requirements survey and recommendations from faculty radiologists, residents, and medical students.BMC medical education · 2025Article
- Physicians and AI in healthcare: insights from a mixed-methods study in Poland on adoption and challenges.Frontiers in digital health · 2025Article
- Knowledge and attitude of medical students towards artificial intelligence in ophthalmology in Riyadh, Saudi Arabia: a cross-sectional study.Annals of medicine and surgery (2012) · 2024Article
- Exploring clinical specialists' perspectives on the future role of AI: evaluating replacement perceptions, benefits, and drawbacks.BMC health services research · 2024Article
- Artificial Intelligence in Healthcare: A Study of Physician Attitudes and Perceptions in Jeddah, Saudi Arabia.Cureus · 2024Article
- Attitude and Understanding of Artificial Intelligence Among Saudi Medical Students: An Online Cross-Sectional Study.Journal of multidisciplinary healthcare · 2024Article
- Attitudes, knowledge, and skills towards artificial intelligence among healthcare students: A systematic review.Health science reports · 2023Article
- Assessing the Level of Understanding (Knowledge) and Awareness of Diagnostic Imaging Students in Ghana on Artificial Intelligence and Its Applications in Medical Imaging.Radiology research and practice · 2023Article
- Perspectives of radiographers on the emergence of artificial intelligence in diagnostic imaging in Saudi Arabia.Insights into imaging · 2022Article
- The Use of Artificial Intelligence in Medical Imaging: A Nationwide Pilot Survey of Trainees in Saudi Arabia.Clinics and practice · 2022Article
- Acceptance of clinical artificial intelligence among physicians and medical students: A systematic review with cross-sectional survey.Frontiers in medicine · 2022Article
- Article
- Artificial Intelligence Readiness Among Jordanian Medical Students: Using Medical Artificial Intelligence Readiness Scale For Medical Students (MAIRS-MS).Journal of medical education and curricular developmentArticle
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
objectivesTo assess the knowledge and perception of artificial intelligence (AI) among radiology residents across Saudi Arabia and assess their interest in learning about AI.
methodsAn observational cross-sectional study carried out among radiology residents enrolled in the Saudi Board of Radiology, Saudi Arabia. An anonymized, self-administered questionnaire was distributed in April 2020 and responses were collected until July 2020.
resultsA total of 154 residents filled the questionnaire. The top 3 aspects of AI participants wanted to learn were: clinical use of AI applications, advantages and limitations of AI applications, and technical methods. Approximately 43.5% of participants did not expect AI to affect job positions, while 42% anticipated that job positions will decrease. Approximately 53% expected a reduction in reporting workload, while 28% expected an increase in workload.
conclusionCurrently, the exposure of radiologists to the use of AI is inadequate. It is imperative that AI is introduced to radiology trainees and that radiologists stay updated with advances in AI to be more knowledgeable on how to benefit from it.
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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.