ArticleRadiologie (Heidelberg, Germany)2026
Exploring AI in radiology: a bibliometric study tailored to a research path.
Article in Radiologie (Heidelberg, Germany), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Radiology has been profoundly transformed by artificial intelligence (AI) over the past decade, enabling automated detection, enhanced diagnostic accuracy, and more personalized patient care. In this study, we performed a bibliometric analysis of the scientific literature on AI in radiology from 2010, aiming to map research trends, identify influential authors and institutions, and uncover emerging thematic areas. Our results show a rapid growth of publications since 2016, with the United States, China, and Germany leading in output. Journals such as the European Journal of Radiology, Academic Radiology, and Clinical Radiology have been the most productive, while keyword analysis revealed emerging topics including explainable AI, multimodal imaging, and AI-assisted clinical decision-making. Collaborative networks among countries and institutions have expanded, reflecting increasing international cooperation. This bibliometric overview highlights the evolving landscape of AI in radiology and provides insights to guide future research and clinical integration.
Indexed as
Identifiers
41775903What OpenQuestion holds
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.