A framework to integrate AI into clinical practice.
At the European Congress of Radiology (ECR) 2026 in Vienna, one shift became impossible to ignore: healthcare AI has moved beyond experimentation and into real clinical infrastructure.
Across presentations, panel discussions and conversations with hospital leaders, the message was consistent. The debate is no longer about whether AI works. Instead, radiology leaders are asking more practical questions: How quickly can we deploy it? How do we scale it across hospitals? And how do we ensure clinicians trust it in everyday workflows?
Aidoc arrived at ECR with significant regulatory momentum. On the eve of the congress, the company announced CE marking under MDR for a comprehensive foundation model–powered AI triage solution.
Powered by CARE™, Aidoc’s foundation model, the solution combines 15 newly cleared indications in a single workflow, covering simultaneous triage of multiple acute findings in CT body examinations during periods of high clinical demand.
The announcement reflects a broader shift discussed throughout ECR: AI is evolving from isolated algorithms into multi-pathology platforms designed for real-world clinical workflows.
Clinical validation remains central to adoption, and several ECR presentations highlighted the real-world impact of AI in time-critical pathways.
At OLVG in Amsterdam, Carolien Toxopeus presented how integrating Aidoc’s AI into trauma imaging workflows improved collaboration between radiologists and emergency clinicians while helping reduce workload and accelerate triage for acute cases.
Meanwhile, researchers from Region Skåne in Sweden shared results from a prospective multicentre study spanning 10 hospitals and more than 3,000 emergency CT angiographies. Aidoc’s stroke AI identified an additional 18.8% of vessel occlusions with a low false-positive rate, demonstrating its value as a complementary tool in emergency stroke workflows.
Scalability was another defining theme at ECR. Germany’s Asklepios Group recently completed one of Europe’s largest clinical AI deployments, rolling out Aidoc’s aiOS™ platform across 28 hospitals. The system now supports clinicians in analysing around 35,000 CT and X-ray scans each month, helping ensure rapid prioritisation of acute findings across the network.
For health systems facing workforce shortages and growing imaging volumes, coordinated, multi-site deployment represents the next phase of AI adoption.
The evolution of AI capabilities was also the focus of a packed panel at Fujifilm House, where Aidoc Chief Medical Officer Jesse Ehrenfeld joined leaders from Radiology Partners, Fujifilm Healthcare Europe and AWS to discuss the shift from foundation models to “agentic radiology.”
The concept reflects a new paradigm: AI that proactively identifies findings and presents them for radiologist validation, helping reduce search fatigue and allowing clinicians to focus on clinical decision-making.
If ECR 2026 demonstrated anything, it is that AI in radiology has reached a turning point. The conversation is no longer about adding more algorithms, but about integrating them intelligently at scale where they can make the greatest difference for patients and care teams.

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