ArticleHealth science reports2025
Exploring Radiographers' Readiness for Artificial Intelligence in Kuwait: Insights and Applications.
Article in Health science reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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
1 citing paper in PubMed.
- Impact of AI Assistance in Pneumothorax Detection on Chest Radiographs Among Readers of Varying Experience.Diagnostics (Basel, Switzerland) · 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
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Introduction: There is a growing adoption of artificial intelligence (AI) in the field of medical imaging. AI can potentially enhance patient care, improve workflow, and analyze patient's medical data. This study aimed to explore radiographers' knowledge, perceptions, and expectations toward integrating AI into medical imaging and to highlight one of the available applications of AI by evaluating an AI-based software that generates chest reports. Methods: A cross-sectional survey was distributed to radiographers ( Results: The survey results showed that most participants agreed that radiographers must adapt the AI technology, and they showed interest in taking courses about AI within radiography (98%, 92%, Conclusion: The study findings identified a need for AI education and training for radiographers to increase their knowledge and improve their ability to use AI. Additionally, the study demonstrated that AI-powered tools are showing great promise in the field of medical imaging.
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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.