ArticleBioinformation2024
Radiologists' perceptions and readiness for integrating artificial intelligence in diagnostic imaging: A survey-based study.
Article in Bioinformation, 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
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
2 citing papers in PubMed.
- Physicians' attitudes and perceptions toward the integration of artificial intelligence into pediatric hematology-oncology in Saudi Arabia.Frontiers in medicine · 2026Article
- Artificial intelligence and breast cancer screening in Serbia: a dual-perspective qualitative study among radiologists and screening-aged women.Frontiers in radiology · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Artificial intelligence (AI) is revolutionizing diagnostic imaging, enhancing precision, speed and efficiency. This study explored radiologists' perceptions of AI through a survey of 100 radiologists across various institutions, focusing on awareness, benefits, concerns and preparedness for AI adoption. Most radiologists recognized AI's potential to improve diagnostic accuracy and workflow efficiency but expressed concerns about its reliability, job displacement and ethical implications. Readiness to adopt AI varied significantly based on age, experience and familiarity with AI tools. These findings underscore the need for targeted education and training programs to address skepticism and support the effective integration of AI into diagnostic imaging practices.
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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.