Course program
Registration for this course is now closed—but there's still time for registrants to continue learning. Registrants can access a live recording of AI Implementation: Building Expertise and Influence in the Online Learning Center through December 31, 2021. Registrants must log in to view the recording.
On-demand access
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 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.
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.
Program presentation times are in GMT.
Day 1: Wednesday, July 21, 2021 2–6 PM Greenwich Mean Time (GMT) 9 AM–1 PM Central Time (CT) |
|||
Time (GMT) | 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 2–6 PM Greenwich Mean Time (GMT) 9 AM–1 PM Central Time (CT) |
|||
Time (GMT) | 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 |