Sessions
Artificial intelligence (AI) is poised to revolutionize radiology training, providing tools for tasks like image interpretation, triaging, reporting, and personalized learning. However, integrating AI into radiology education requires addressing diverse perspectives from stakeholders such as attendings, residents, fellows, medical students, and researchers. Tailored AI-enhanced curricula and best practice guidelines are essential to meet these needs…
As the field of medical imaging evolves, the integration of multi-agent large language models (LLMs) presents groundbreaking opportunities to enhance diagnostic accuracy and streamline clinical workflows. This interactive session provides a deep dive into how multi-agent LLMs collaborate to process and analyze medical imaging data, from system construction to real-world optimization. Attendees will gain hands-on…
Enhancing Imaging Appropriateness in Acute Care: Aligning Large Language Models with the American College of Radiology Appropriateness Criteria Hersh Sagreiya, MD, Assistant Professor of Radiology, Radiology, University of Pennsylvania Michael Yao; Charles Kahn, MD, MS, FACR; Walter Witschey, PhD; James Gee, PhD; Osbert Bastani, PhD; Allison Chae Evaluating Large Language Models for Multi-Institutional Radiology…
“If you don’t know where you are going, you’ll end up somewhere else.” - Yogi Berra Are you an aspiring woman leader who wants to unlock your unique power and level up in your imaging informatics career? Are you interested in exploring how to connect your leadership with your core values and develop an…
