ArticleInternational journal of general medicine2024
Radiologic Technology Students' Perceptions on Adoption of Artificial Intelligence Technology in Radiology.
Article in International journal of general medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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
2 citing papers in PubMed.
- AI Integration in Medical Imaging Education: A Nationwide Cross-Sectional Survey.Radiology research and practice · 2026Article
- Artificial intelligence for diagnostics in radiology practice: a rapid systematic scoping review.EClinicalMedicine · 2025Article
Corrections and comments
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Authors and funding
1 author.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Study Purpose: This study aims to analyze radiologic technology student's perceptions of artificial intelligence (AI) and its applications in radiology. Methods: A quantitative cross-sectional survey was conducted. A pre-validated survey questionnaire with 17 items related to students perceptions of AI and its applications was used. The sample included radiologic technology students from three universities in Saudi Arabia. The survey was conducted online for several weeks, resulting in a sample of 280 radiologic technology students. Results: Of the participants, 63.9% were aware of AI and its applications. T-tests revealed a statistically significant difference (p = 0.0471) between genders with male participants reflecting slightly higher AI awareness than female participants. Regarding the choice of radiology as specialization, 35% of the participants stated that they would not choose radiology, whereas 65% preferred it. Approximately 56% of the participants expressed concerns about the potential replacement of radiology technologists with AI, and 62.1% strongly agreed on the necessity of incorporating known ethical principles into AI. Conclusion: The findings reflect a positive evaluation of the applications of this technology, which is attributed to its essential support role. However, tailored education and training programs are necessary to prepare future healthcare professionals for the increasing role of AI in medical sciences.
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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.