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Aug 2, 2011
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Latest in Imaging Informatics
Prof. Raj Jena of the University of Cambridge.
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Data from the 3R Swiss Imaging Network indicates that while 91% of radiologists use AI, successful adoption depends heavily on full workflow integration.
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More in Imaging Informatics
RCR appoints Raj Jena to oncology AI post
By AuntMinnieEurope.com staff writers
Jena was the U.K.'s first professor of AI in radiotherapy.
May 7, 2026
Prof. Raj Jena of the University of Cambridge.
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The five-year experiment: real-world lessons from 400,000 AI-processed imaging studies
By Claudia Tschabuschnig
AI models are the easy part. Governance, integration, and real-world workflows decide what survives, according to insights from five years of implementation across 20 imaging centers.
April 28, 2026
Data from the 3R Swiss Imaging Network indicates that while 91% of radiologists use AI, successful adoption depends heavily on full workflow integration.
AI model predicts cardiovascular risk from BACs on mammograms
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An AI model showed success in using age-adjusted breast arterial calcifications from mammograms to predict cardiovascular events.
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Example of Percentile Nomogram With Age-Adjusted BAC Quartiles. (A) Mammogram of a 56-year-old woman. There is evident BAC (pink arrow). This was quantified as a BAC score of 30 using the cmAngio tool. (B) Nomogram indicating that a BAC score of 30 places a 56-year-old woman within the 50th to 75th percentile for her age. Images are republished under a Creative Commons license (CC BY 4.0).
"You'll never walk alone": Benoît Rizk on how to make radiology AI work
By Claudia Tschabuschnig
At 3R Swiss Imaging Network, Dr. Benoît Rizk works at the center of real-world AI in radiology. In this video interview he shares why governance and integration matter more than the models themselves, and why the profession needs to have an honest conversation about the decade ahead.
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New x-ray dataset helps clinicians develop pathology detection AI
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ICUs rely heavily on bedside chest x-ray to monitor patients, and the dataset could offer support for radiologic assessment.
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Example radiographs with different labels for 'pulmonary congestion,' 'pleural effusion,' 'pulmonary opacities,' and 'atelectasis.'
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GPT-4o matches experienced radiologists for follow-up imaging recs
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The AI model matched the performance of radiologist readers in recommending follow-up imaging from routine radiology reports.
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