3 can't-miss AI sessions at RSNA 2019

RSNA 2019, the world’s largest radiology conference, kicks off at Chicago’s McCormick Place on Sunday, Dec. 1, and promises to include more AI content than ever before. There will be an expanded AI Showcase this year, giving attendees access to more than 100 vendors in one location.

While it’s impossible to experience every single part of RSNA 2019 related to AI—unless you’re a fully functional robot yourself, I suppose—there are a few educational sessions I do highly recommend you attend. They are:

1. “Artificial Intelligence and Precision Education: How AI Can Revolutionize Training in Radiology” | Monday, Dec. 2 | 8:30 – 10 a.m. | Room: E450A

Attendees should make sure they wake up bright and early Monday morning and make their way to this session, which includes three separate presentations on AI and radiology. The first presentation, from moderator Falgun H. Chokshi, MD, examines the “basics” of machine learning and AI, including its limitations and how it might impact medical imaging in the years ahead.

Soonmee Cha, MD, a professor in residence of radiology and neurological surgery at the University of California, San Francisco, will be delivering the second presentation, “State of Radiology Education: Opportunities for Change.” Techniques for training the next generation of radiologists about AI will—and ways to “educate the educators”—will be discussed at length.

The session is scheduled to end with a panel, giving attendees the opportunity to hear tips and advice about AI from five participants who come from a variety of backgrounds.  

2. “Learning AI from the Experts: Becoming an AI Leader in Global Radiology (Without Needing a Computer Science Degree)” | Tuesday, Dec. 3 | 4:30-6 p.m. | Room: S406B

This 90-minute session includes five different presentations aimed at helping radiologists gain a better understanding of AI. Topics include differentiating AI from global radiology and how radiologists can “get a seat at the table” when it comes to developing implementing AI policies.

The always-fascinating Eliot L. Siegel, MD, is sure to be a highlight with his presentation, “Understanding AI: How Does that Black Box (AI) Work?”

3. “Deep Learning in Radiology: How Do We Do It?” | Wednesday, Dec. 4 | 8:30-10 a.m. | Room: S406B

This session puts the spotlight on deep learning, one of the single most important topics for radiologists to study when it comes to AI. Expect a crowded room for this one—get there early Wednesday morning if you want a good seat!

Luciano M. Prevedello, MD, MPH, will be moderating the session and discussing the use of deep learning at Ohio State University. There will also be detailed descriptions of how deep learning has been developed and implemented at both Stanford University and Mayo Clinic.

This, to me, is perhaps the most exciting part of RSNA 2019 compared to past shows in Chicago—the fact that providers now have real experiences to share. At first, a lot of discussions surrounding AI were about its potential and not about what it was actually like to use these groundbreaking technologies. In 2019, however, things have started to finally shift as more and more radiologists throughout the world are getting their hands dirty and experiencing it for themselves.

Need more details? Click here for RSNA 2019's full schedule.