ArticleWorld journal of radiology2026
Expanding the applications of artificial intelligence in emergency radiology: Advancing precision medicine and resource efficiency.
Article in World journal of radiology, 2026. 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.
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Who cites it
1 citing paper in PubMed.
Corrections and comments
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Owing to their swift, precise, and tireless capabilities, artificial intelligence (AI) applications in emergency radiology are becoming powerful tools for radiologists. These applications, which are useful for improving diagnostic efficiency, are also a core engine driving the entire field of emergency medicine toward higher levels of precision, personalization, and efficiency. The integration of AI into emergency radiology thus represents a transformative advancement in precision medicine. We explore herein the expanding applications of AI in emergency radiology, focusing on their potential to enhance diagnostic accuracy, streamline workflows, and improve patient outcomes. By analyzing its current utilization and future directions, we demonstrate how AI is revolutionizing emergency care through intelligent image analysis and decision support systems. Although certain challenges remain, including data security, model interpretability, and clinical implementation standards, the immense potential of AI to reshape emergency workflows, promote precision medicine, and improve patient outcomes is unmistakable.
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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 Socratic graph.