Become your institution’s AI influencer and learn how to translate AI concepts and theories into everyday clinical practice at AI Implementation: Building Expertise and Influence.

During this two day, in-person workshop you’ll learn alongside expert faculty and build the basic knowledge you need to evaluate AI's complexities, advantages and limitations.

You’ll also participate in expert-led group exercises, where you’ll develop basic AI models and evaluate the key elements needed to successfully integrate AI into your institution’s workflows.

Review the course information below and register today — space is limited!

Course faculty   Course registration
Who should attend this course?

Practicing radiologists from academic and private practices in all career stages and subspecialties interested in developing foundational-level AI knowledge in a small-group setting can benefit from this course.

Course information

This interactive, English-language course will take place May 26–27 in London and will provide lectures, panel discussions, hands-on demonstrations and small-group exercises to help radiologists:

  • Understand ethical, legal and practical considerations before adopting AI
  • Build a foundational knowledge base in order to evaluate AI’s advantages and limitations
  • Transition from theory to practice in order to successfully implement solutions into everyday workflows
  • Understand how to select an appropriate vendor in order to facilitate AI implementation alongside your institution’s management
  • Differentiate between promotional marketing language and the real-world value of AI products
Learning objectives

After attending this course, participants will be able to:

  • Identify learning strategies to translate practical theories in AI into clinical practice.
  • Explain the current clinical applications of deep learning in radiology.
  • Examine the pre-implementation and implementation complexities, including ethical, legal and social implications before adopting AI into a radiology practice.
  • Construct a grounded outlook on the current limitations and future possibilities in radiology AI.

ACCME Accreditation Statement: The Radiological Society of North America (RSNA) is accredited by the Accreditation Council for Continuing Medical Education (ACCME) to provide continuing medical education for physicians. 

Credit Designation Statement: RSNA designates this Live Education activity for a maximum of 8.00 AMA PRA Category 1 Credit™. Physicians should claim only the credit commensurate with the extent of their participation in the activity.

Program preview
Friday, May 26 | 9 a.m. – 6 p.m.
Course Welcome and Introduction
Foundations of AI in Medical Imaging: Traditional Machine Learning, Deep Learning and Recent Advancements
Networking and coffee break
From Theory to Practice: Guided Hands-on Experience
Lunch Break
Interactive Pre-Implementation Exercise
Networking and Coffee Break
Interactive Pre-Implementation Exercise
Networking Reception & Meet the Experts
Saturday, May 27 | 9 a.m. – 12 p.m.
Interactive Post-Implementation and Post-Market Surveillance Exercise
Networking and Coffee Break
Current Limitations and Considerations for the Future
Closing Remarks

This schedule is subject to change.

Contact us

Questions? Contact us at customerservice@rsna.org.