Event Speaker
Paul Yi,
MD, MS
Radiologist
St. Jude Children's Research Hospital
Paul Yi, MD is Director of the University of Maryland Medical Intelligent Imaging (UM2ii) Center and Assistant Professor of Diagnostic Radiology and Nuclear Medicine. He is also Adjunct Research Scientist at the Johns Hopkins Malone Center for Engineering in Healthcare. Dr. Yi received his BA in Medical Sciences (Summa Cum Laude) and MD from Boston University through the Seven-Year Accelerated Medical Program. Prior to a career in Radiology, he completed 2 years of Orthopaedic Surgery residency training at the University of California, San Francisco (UCSF). He completed his radiology residency in 2020 and musculoskeletal imaging fellowship in 2021, both at Johns Hopkins, as well as an Imaging Informatics Fellowship at the University of Maryland in 2020. He is the recipient of numerous national research awards, both within the fields of Radiology and Orthopaedic Surgery, including Cum Laude awards from the Radiological Society of North America (RSNA) and American Roentgen Ray Society (ARRS) and the Frank Stinchfield Award from the Hip Society. He has published over 90 articles in the peer-reviewed medical literature and his research has been supported by the RSNA and Johns Hopkins University Discovery Award. As a practicing physician-scientist, his current research interests include the development and application of AI and deep learning towards medical imaging applications, with special interest in evaluating the trustworthiness and fairness of deep learning models.
Sessions
Bridging the Gap: Mitigating Bias, Building Trust, and Mastering Human-AI Collaboration
As artificial intelligence continues to reshape the healthcare landscape, understanding the human element of AI interaction is essential. This session explores strategies for identifying and mitigating biases in AI systems, fostering trust between users and technology, and providing effective education and training to ensure clinicians can confidently interpret and apply AI insights. Participants will leave…
Cracking the Code: Technical Deep Dive into Multimodal Foundation Models for Medical Imaging
Multimodal foundation models are rapidly emerging as a transformative force in enterprise imaging—but their underlying mechanics and clinical implications often remain misunderstood. This session delivers a technical deep dive into how these models integrate visual, textual, and structured data to advance diagnostic imaging. Attendees will explore cutting-edge research, learn about the architectural foundations of state-of-the-art…
First Time Attendee Meetup
Welcome to SIIM! If you're a first-time attendee at the SIIM Annual Meeting, navigating the experience might feel a bit daunting. Join SIIM leadership, comprising both the Board and Program Committee, as they guide you through an insightful discussion about what to anticipate during the annual meeting. Gain insights into the event layout and discover…