Agentic AI has the potential to redefine radiology by evolving beyond traditional workflows into more autonomous, interconnected, and adaptive pipelines—enhancing efficiency, improving quality, and reducing the burden on radiologists. But what exactly is Agentic AI? How does it work, and how can it be applied in radiology? This webinar brings together experts for an engaging discussion on the capabilities, limitations, and future of Agentic AI in medical imaging.

The panelists will explore key topics such as what differentiates an agentic workflow, how they work, how large language models (LLMs) have evolved to support AI Agents, and the real-world applications. The session will also examine emerging trends, potential challenges, and expectations for the future of AI-driven radiology. Attendees will gain valuable insights into where Agentic AI stands today and how it may shape the next generation of medical imaging workflows.

Objectives

  • Discuss the foundations and types of Agentic AI in radiology.
  • Explore real-world use cases demonstrating AI Agent impact on radiology workflows.
  • Identify challenges and considerations for adopting AI Agents in clinical settings.

CE Credit

SIIM has approved this activity for 1.0 hours of SIIM IIP Credits towards certification and re-certification by the American Board of Imaging Informatics (ABII).

To receive credit, registrants must view the entire webinar and then complete the post-webinar survey. Webinar credits will only be awarded one time per webinar view, regardless of if the learner watches the content live or on-demand.

Note: In order to receive credits for any events/learning you attend you must select your eligible credit types found in the CE & Certification section of your MySIIM Account profile.

To access the webinar, once you are registered navigate to My Learning in your My SIIM Account profile.    

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DATE

May 12, 2025

Time

12:00 pm - 1:00 pm (ET)

Credit Amount

1.0

Credit Type

IIP

Non-Member Cost

$30

Member Cost

$0

Delivery Type

  • Virtual-Live

Audience Type

  • Clinician
  • Imaging IT
  • Researcher/Scientist
  • Student Member in Training (SMIT)
  • Vendor

Register

Speakers

Imon Banerjee, PhD

Associate Professor of Radiology

Mayo Clinic, Phoenix, Arizona

Paulo Kuriki, MD

Assistant Professor of Radiology, Director, AI Lab

UT Southwestern Medical Center

George Shih, MD, MS

Associate Professor of Radiology, Vice Chair for Informatics

Weill Cornell Medicine

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