Raidium invites you to their event

Raidium | Usage & perspectives of AI in radiology

About this event

AI that drafts radiology reports is here. The next question is what happens when AI can plan, use tools, gather context, and act across the entire diagnostic workflow.


Join Raidium and a panel of radiologists and industry experts for a candid, moderated discussion on what agentic AI really means for radiology: where the promise is real, where the hype outruns practice, and what today’s draft-generation solutions still lack.


What we’ll discuss:

  • What “agentic” actually means for radiology, and why it may be a new wave of diagnostic technology rather than another incremental step.
  • Draft report generation: promise and limits. What helps in daily reading, what adds friction, and what builds or breaks trust.
  • The ideal PACS and diagnostic tool, and how agentic AI compares with earlier technology shifts such as client-server and the cloud.
  • What’s missing today, including clinical context beyond the image, automation bias, traceability, uncertainty handling, workflow integration, and feedback loops. Raidium will share its approach to agent orchestration.
  • Trust, governance, and adoption: keeping radiologists in control, validating multi-agent systems, and the questions of infrastructure and compute that increasingly shape who can deploy AI.
  • A look ahead: what a radiologist’s day might look like in three years.

Who should attend:

Radiologists and imaging leaders, healthcare IT and innovation teams, and industry and investment professionals following AI in medical imaging. No technical background required.

Hosted by

  • External speaker
    E
    Amine Korchi Radiologist, Investor & Advisor
  • External speaker
    E
    Ludovic D'Apréa Strategic Advisor @ Raidium
  • External speaker
    E
    Curtis Langlotz Professor of Radiology @ Standford
  • External speaker
    E
    Paul Herent CMO & Co-founder @ Raidium

Raidium

The AGI company

Raidium develops the first 3D Foundation Models for precision radiology. It is delivered to radiologists through an AI-native PACS viewer, enabling direct interaction with the model, like a radiology copilot. Initial applications focus on oncology, before expanding to the broader radiology workflow.