Town Hall: Making AI a Success at Scale
Machine Learning (ML) and Artificial Intelligence (AI) are rapidly transforming the field of imaging. Leading academic medical centers, large private radiology practices, teleradiology providers, and federal health systems are successfully integrating AI algorithms into their clinical workflows at scale.
This town hall will bring together experts who have implemented a variety of AI solutions, including commercial products, internally developed algorithms, and hybrid approaches. They will share their experiences and insights on how to overcome the unique challenges of scaling AI in complex imaging environments.
Join us for an interactive discussion on how to make AI a success in your imaging practice.
Objectives
Success stories: Hear real-world examples of how AI is improving efficiency, accuracy, and patient outcomes in imaging
Lessons learned: Gain insights on best practices for implementing and scaling AI, including data management, algorithm selection, and change management
Challenges and solutions: Learn how to address common obstacles, such as regulatory compliance, integration with existing systems, and physician adoption
The future of AI in imaging: Discuss emerging trends and technologies that will shape the future of AI-powered imaging
Speakers
Brian Baker
Senior Director of Software Engineering
vRad
Peter D. Chang, MD
Associate Professor, Radiological Sciences and Computer Science, University of California, Irvine
Director, UCI Center for AI in Diagnostic Medicine
John Hoy, MD
Chair
VISN Enterprise Radiology
Nina Kottler, MD, MS, FSIIM
Associate CMO, Clinical AI
Radiology Partners
Greg Sorensen, MD
Chief Science Officer, Radnet
Co-Founder & CEO, DeepHealth
Session Chair
Katherine P. Andriole, PhD, FSIIM
Associate Professor of Radiology, BWH, Harvard Medical School
Director of Research Strategy & Operations, MGH & BWH Center for Clinical Data Science
