As radiologists learn how to incorporate AI into their everyday practice and workflow, RSNA is expanding its Imaging AI Certificate Program with a subspecialty specific curriculum that blends learning with practical application.
“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,” said Marta E. Heilbrun, MD, certificate course advisor and medical director, Imaging Services, Quality & Patient Safety at Intermountain Health, Salt Lake City, UT. “Some of the most mature radiology AI applications have been developed for use in emergency imaging.”
AI in Emergency Imaging Can Expedite Diagnosis
Radiologists working in the ED are required to provide quick report turnarounds, manage high reading demands and be versed in many subspecialty areas.
The RSNA Emergency Imaging AI Certificate course will provide radiologists with support to meet these particular demands.
“The course is designed to enable participants to evaluate, deploy, monitor and use AI tools in emergency imaging,” said Po-Hao “Howard” Chen, MD, MBA, certificate course director and vice chair of diagnostics institute and assistant professor of radiology at Cleveland Clinic Lerner College of Medicine at Case Western Reserve University, Cleveland. “With modules on evaluating AI and critical communication, as well as detailed focus on AI for triage and radiology efficiency, attendees should come away with practical solutions to address challenges in emergency imaging.”
The course will help radiologists use AI to increase efficiency during high demand moments, leverage AI to write reports that lead to actionable results and use AI to support triage, including rapid image analysis, prioritization and early detection of critical conditions.
Dr. Chen discusses how the Emergency Imaging in AI Certificate will benefit patient care:
The course will introduce concepts that are central to evaluating AI models from various essential perspectives, such as business, clinical and IT, according to Dr. Chen.
“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,” Dr. Chen said. “Moreover, the course will cover critical 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.”
Participants will also find that the Emergency Imaging AI Certificate will offer solutions to expedite the overall diagnostic process and increase diagnostic accuracy, improve communication and collaboration among health care team members and help integrate point-of-care imaging devices, allowing for immediate analysis of images acquired at the bedside.
“AI is ideally positioned to support radiologists in the fast-paced environment of emergency imaging. Given the urgent nature of this work along with the global trend of workloads surpassing radiologist capacity, AI has become critical in ensuring efficient and timely triage and care coordination,” said Nina Kottler, MD, MS, certificate course director and associate chief medical office, Clinical AI and vice president clinical operations at Radiology Partners in Rancho Santa Fe, CA. “The use of AI has twofold benefits: the enablement of more timely treatment to critically ill patients has been shown to improve patient outcomes; and generative language models and natural language processing technologies can also help radiologists manage their workday with reduced cognitive strain and improved reporting efficiency.”
Watch Dr. Kottler discuss why it’s important for radiologists to incorporate AI into their workflow and every day practice:
Certificate Offers Practical Implementation Tips
The Emergency Imaging AI Certificate is designed for radiology professionals who are leading the implementation of AI solutions in clinical, emergency settings. It does not require prerequisite completion of the RSNA Imaging AI Foundational Certificate course or the Advanced Certificate course, although these can provide broad AI knowledge and a deeper understanding of how to deploy, monitor and use AI algorithms within clinical practice.
The Emergency Imaging AI Certificate course, presented in six on-demand online modules, will briefly review some of the concepts covered in the Foundational Certificate and additional content that is explored in detail in the Advanced Certificate course will be included.
The modules will offer practical teaching and practice that will lay the groundwork for using AI in emergency imaging. Bite-sized didactic lectures will be augmented by hands-on experiential learning.
“Participants will gain expertise in the application of AI in emergency imaging, which is essential for modern radiological practice and, most importantly develop skills in evaluating AI, helping them to become the clinical champion for bringing AI into their emergency radiology practice,” Dr. Chen said.
“AI has already entered the radiology vernacular and will play a significant role in the evolution of diagnostic radiology,” Dr. Kottler said. “Individuals who grasp the capabilities and limitations of AI have the power to influence its application and effectively engage in conversations about, evaluate, critique and deploy AI models in emergency radiology.”