News | Artificial Intelligence | March 05, 2019

RSNA Offers First U.S. Spotlight Course on Artificial Intelligence

“Radiology in the Age of AI” will explore the role of AI throughout the image cycle, basic tools and techniques

RSNA Offers First U.S. Spotlight Course on Artificial Intelligence

March 5, 2019 – The Radiological Society of North America (RSNA) announced an expansion of its artificial intelligence (AI) education with two new regional courses this spring, including the first RSNA Spotlight course to be held in the U.S. The society will bring together top AI experts and knowledgeable industry professionals in an intimate, professional setting to deliver the latest, most practical AI insights through sessions and panel discussions.

“Radiology in the Age of AI,” will take place May 31-June 1, 2019, in San Francisco. This two-day course explores the role of AI throughout the image life cycle. The course will provide a one-of-a-kind opportunity for attendees to talk to the top minds in AI and discover what this rapidly advancing technology will mean for their clinical practice. Attendees will be able to interact with industry partners and leaders to explore the latest progress in clinically useful AI systems, as well as basic AI tools and techniques non-computer scientists can use to better understand AI research.

“As radiologists move beyond fear of job displacement and into the ‘show me’ phase, this course provides the information they need to make decisions about the adoption of AI technology,” said Curtis P. Langlotz, M.D., Ph.D., RSNA board liaison for informatics.

The course will be taught by a slate of thought leaders in AI and features two keynote speakers.

Andrew Ng, Ph.D., CEO of Landing AI and a general partner at AI Fund, will deliver the keynote address, “AI is the New Electricity: The Disruptive Power of AI Applications in Medical Imaging.” Lloyd B. Minor, M.D., the Carl and Elizabeth Naumann Dean of the Stanford University School of Medicine will present the second keynote, “Digitally Driven: Health Care in the Era of Precision Health.”

Course directors are Udo Hoffmann, M.D., MPH, professor of radiology at Harvard Medical School, chief of the Division of Cardiovascular Imaging at Massachusetts General Hospital (MGH) in Boston, Mass., and the director of the MGH Cardiac MR PET CT Program, and Matthew P. Lungren, M.D., MPH, associate director of the Stanford Center for Artificial Intelligence in Medicine and Imaging, and assistant professor and clinician scientist at Stanford University Medical Center.

After attending this course, participants will be able to:

  • Review the origins of AI and its application to medical imaging;
  • Demonstrate the role of AI throughout the image life cycle, including image creation, quality control, triage, detection, differential diagnosis and reporting;
  • Understand the basic tools and techniques for AI and machine learning and their pitfalls;
  • Assess the progress toward clinically useful AI systems; and
  • Learn how non-computer scientists can read and understand an AI paper and evaluate the clinical applicability of AI algorithms

Course program details and faculty are available here. Early-bird registration ends March 15.

Another regional AI course, “Comprehensive AI for Practicing Radiologists,” will be held May 3-4, 2019, in Paris, France.

This course, presented in English, is designed specifically for practicing radiologists, providing the tools they need to become AI adopters. Top AI experts will teach course participants useful skills for integrating AI into practice workflows and processes, ultimately enhancing patient care.

The course is presented under the direction of Nabile M. Safdar, M.D., MPH, associate CMIO at Emory Healthcare and vice chair of informatics in the Department of Radiology and Imaging Sciences at Emory University in Atlanta, Ga.; and Marc Zins, M.D., chairman of the Radiology Department at Saint Joseph Hospital, René Descartes University in Paris, France.

“This course gives radiologists the foundation to truly understand what applying AI in their clinical practice means,” Safdar said.

For more information: www.rsna.org

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