Beyond Accuracy: A Framework for Trustworthy Radiology AI Validation

Most certified radiology AI tools are approved, but not validated. While evidence is growing, studies still focus mainly on technical accuracy, leaving critical questions about outcomes, workflow integration, and governance unanswered.

In this webinar, experts present findings from a recent European Radiology study on 173 CE-certified AI tools and share a vendor-neutral framework for deciding which type of validation is needed at which stage.

Learn why vendor-neutral validation is essential for clinical trust, institutional governance, and national strategies. Whether you are a radiologist, policymaker, or innovation leader, this session provides the tools to move beyond promises to real-world proof.

Certified is not the finish line: make validation proportional to risk
Understand why certification does not prove real-world performance and how to apply a risk and evidence-based approach to validation and monitoring across sites and populations.

‍Evidence from the largest review of radiology AI validation to dateSee findings from the European Radiology study of 173 CE-certified AI tools, highlighting both the growth in peer-reviewed validation studies and the persistent gaps in outcome-level, vendor-independent, and prospective evidence.

A vendor-neutral framework for validation
Discover a structured approach to determine which type of validation (technical, clinical, operational, or socio-economic) is needed at each stage, with examples of how hospitals and researchers can apply this in real-world settings.

Fireside chat on clinical practice, governance, and policy
Hear experts discuss how clinicians can interpret and challenge vendor evidence, how vendor-neutral validation supports governance and national AI strategies, and what lessons policymakers and innovation leaders can use to build trust in adoption.