ArticleJournal of imaging informatics in medicine2026
AI as Core Infrastructure in Radiology: Moving Beyond Pilots to Operational Excellence.
Article in Journal of imaging informatics in medicine, 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
1 author.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Artificial intelligence (AI) adoption in radiology has accelerated, but operational maturity has not kept pace. Many organisations still deploy AI as isolated point solutions, leading to fragmented workflows, duplicated integration work, inconsistent governance, unclear accountability, and limited ability to assess value over time. For radiologist-facing clinical AI, these problems are less about model performance alone and more about how AI is introduced, integrated, and managed in practice. This commentary argues that radiology should treat AI not as a collection of disconnected products, but as a managed operational capability supported by shared governance, integration, measurement, and continuous oversight. A practical six-part framework is proposed: clinical intent, workflow orchestration, integration architecture, governance and safety, measurement and analytics, and continuous improvement. A 90-day roadmap is also presented to help imaging leaders move from scattered pilots to repeatable operational deployment.
Indexed as
Identifiers
42557431What Socratic 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 Socratic graph.