Course program

Build a foundational knowledge of artificial intelligence (AI) and equip yourself with the expertise to effectively implement AI at your practice and create a more productive workplace. This two-day, virtual course led by AI experts will help you better understand deep learning and to confidently make decisions around vendor selection.

During this course, participants will attend a live demo, participate in small group discussions and network with peers and presenters.

Space is limited—be sure to save your spot for AI Implementation: Building Expertise and Influence today!

Learning objectives

After attending this course, participants will be able to:

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

AMA Credit Statement

The RSNA designates this live activity for a maximum of 7.50 AMA PRA Category 1 Credits™. Physicians should claim only the credit commensurate with the extent of their participation in the activity.

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.

Register

Day 1: Wednesday, July 21, 2021
Greenwich Mean Time (GMT)
Time Presentation Title
2:00 - 2:15 PM Welcome
2:15 - 3:15 PM Foundations of AI in Medical Imaging: Traditional Machine Learning, Deep Learning and Recent Advancements
  20 minutes What is Deep Learning, How it Differs from Traditional Machine Learning Methods and How Does it Work? - Marc Kohli, MD
  20 minutes Deep Learning Applications in Medical Imaging - Po-Hao Chen, MD
  20 minutes How to Find the Substance in the Hype? - Yan Chen, PhD
3:15 - 4:15 PM From Theory to Practice: Live demonstration - Luciano M. Prevedello, MD; Felipe Campos Kitamura, MD
4:15 - 4:30 PM Break
4:30 - 6:00 PM Pre-implementation exercise
  5 minutes Introduction
  40 minutes Small group exercise
  40 minutes Group report outs
 
Day 2: Thursday, July 22, 2021
Greenwich Mean Time (GMT)
Time Presentation Title
2:00 - 2:15 PM Welcome
2:15 - 3:45 PM Implementation exercise
  5 minutes Introduction
  45 minutes Small group exercise
  40 minutes Group report outs
3:45 - 4:00 PM Break
4:00 - 5:00 PM Current Limitations and Considerations for the Future
  30 minutes Review of Current Limitations and Future Perspectives in Machine Learning in Medical Imaging - Nisha Sharma, MBChB
  30 minutes Panel discussion - All faculty
5:00 - 6:00 PM Meet the experts/Networking session

Register