RSNA Launches New AI Certificate Course in Emergency Imaging

OAK BROOK, Ill. (January 17, 2024) — The Radiological Society of North America (RSNA) is launching a new artificial intelligence (AI) certificate course, focusing on emergency imaging. Following the successful rollouts of the RSNA Imaging AI Foundational Certificate in 2022 and the Advanced Certificate in 2023, the RSNA Emergency Imaging AI Certificate course is the third certificate course developed by RSNA.

"A key goal in RSNA's current strategic plan is to be recognized as an indispensable source of information about radiologic science and practice," said course director Marta Heilbrun, M.D., medical director of Imaging Services, Quality & Patient Safety at Intermountain Health in Salt Lake City, Utah. "The vast majority of practicing radiologists are involved with emergency imaging in some aspect of their practice. The diagnostic and workflow challenges encountered in emergency imaging are prime opportunities for disruptive technologies like AI. Some of the most mature radiology AI applications have been developed for use in emergency imaging. For these reasons, we identified emergency imaging for this new AI Certificate with a subspeciality focus."

The RSNA Emergency Imaging AI Certificate course is designed to help radiology professionals build skills to leverage AI in emergency clinical settings to improve efficiency and patient outcomes.

"The course is set to introduce concepts that are central to evaluating AI models from various essential perspectives, such as business, clinical, and IT," said course director Po-Hao "Howard" Chen, M.D., M.B.A., vice chair of Diagnostics Institute and assistant professor of radiology at Cleveland Clinic Lerner College of Medicine at Case Western Reserve University in Cleveland, Ohio. "Attendees will learn how to assess the impact of AI tools not only on patient care but also on the operational and technological aspects of emergency radiology. Moreover, the course will cover important topics like ensuring appropriate follow-up actions and effectively communicating critical findings, which are crucial for the integration of AI into the emergency imaging workflow."

The RSNA Emergency Imaging AI Certificate course provides a focused look at imaging AI for those implementing AI in a clinical setting, especially early career radiologists and trainees. The course is well suited for radiology professionals handling cases that are considered urgent or emergent in nature, as well as cases in environments that require immediate triage.

The curriculum is case-based and consists of six modules plus a fireside chat, featuring expert instructors that provide a deeper understanding of the steps involved in using AI algorithms in medical imaging.

The first module is available now. New modules will be released monthly through June 2024 and will be available on demand. Modules include brief didactic lectures and independent, hands-on exercises to help participants practice and apply what they learn.

"AI has already entered the radiology vernacular and will play a significant role in the evolution of diagnostic radiology," said course director Nina Kottler, M.D., M.S., associate chief medical officer of clinical AI, and vice president of clinical operations at Radiology Partners in Rancho Santa Fe, California. " Individuals who grasp the capabilities and limitations of AI have the power to influence its application. Understanding the mechanics of AI models and leveraging this knowledge to inform users is key to harnessing AI's full potential. This course is designed to equip participants with the necessary resources to effectively engage in conversations about, evaluate, critique, and deploy AI models in emergency radiology."

In addition to the Emergency Imaging AI Certificate course, the RSNA Imaging AI Certificate Program offers Foundational and Advanced Certificate courses, providing participants with the ability to harness the AI knowledge critical to meeting the challenges in the medical imaging field.

The Foundational Certificate course was developed to help radiology professionals learn how to confidently evaluate, deploy, monitor and use AI tools. The Advanced Certificate course was designed to help participants understand AI model development, evaluate the fairness of AI models across populations and examine the pitfalls of dataset curation, pre-processing and annotation in a clinical setting.

Foundational and Advanced Certificates are not prerequisites for the Emergency Imaging AI Certificate.

Enrollment information for all the RSNA Imaging AI Certificate courses can be found at RSNA.org/AI-Certificate.