A coordinated effort among the federal government, academia, and industry is essential to prepare for advances in AI systems that are poised to transform imaging research.
- How can stakeholders proactively leverage and prepare for advances in AI systems that may fundamentally change imaging research and its applications?
- What infrastructure investments, organizational models, and workforce development strategies are required to realize these capabilities while maintaining scientific rigor, transparency, and research integrity?
- How do academic researchers contribute to AI foundation models and algorithms, while balancing increasing clinical demands?
- What governance frameworks and evaluation processes are needed to ensure AI algorithms are appropriately monitored, validated, and re-evaluated over time?
- What responsibilities do each of the respective stakeholders have regarding AI’s further advancement in radiology and imaging research?
Discussion Leads:
Mark Anastasio, PhD, Vice Chair, Imaging Sciences and AI Research; Mallinckrodt Endowed Professor in Imaging Sciences; Director, Center for Computational and AI-Enabled Imaging Sciences, Washington University in St. Louis
Katherine Andriole, PhD, Associate Dean for Health Artificial Intelligence (AI) Strategy and Innovation, University of California at Los Angeles (UCLA); Director for the UCLA Center for AI and SMART Health; Professor of Radiological Sciences and Bioengineering
Tessa Cook, MD, PhD, Associate Professor of Radiology, Vice Chair of Practice Transformation, University of Pennsylvania
Judy Gichoya, MD, MS, Associate Professor of Interventional Radiology & Informatics, Emory University