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Implementing & Evaluation AI in Radiology. Learn from radiologists how they navigate clinical AI selection.

screen of what a radiologist medical viewer
Softneta Meddream medical imaging viewer

March 14 & March 2024

Asher Informatics is a proud sponsor of an RSNA Spotlight course that helps radiologists navigate AI solutions for radiology and get the practical, relevant information clients need to make informed implementation decisions for your practice. John F Kalafut, PhD will present his expertise, explore use cases, lessons learned and important considerations before selecting an AI solution following the Course Directors who represent some of the biggest thought leaders in Clinical AI adoption.

During this two-day, virtual course, attendees gain an in-depth understanding of AI research concepts, products and deployment challenges. Plus, you’ll develop the critical evaluation skills you need to contribute to the ongoing integration of AI tools in clinical practice.

With the number of clinical AI solutions increasing and the number of government and society best practices coming out with AI Governance guidelines, implementing and evaluating AI is getting more challenging. How radiologists navigate their clinical AI choices is changing. It is no longer feasible to run 6-month pilot programs as there are too many choices, and they cannot look at what their competitors are using because data, infrastructure and integration will all affect performance and adoption.

Radiologist Learning Objectives:

  • Explore radiology use cases for AI 

  • Identify common applications of AI in radiology, such as image interpretation, disease detection and workflow optimization. 

  • Integration into clinical workflow 

  • Evaluate strategies for integrating AI systems into existing radiology workflows. 

  • Address regulatory and ethical considerations when deploying AI in clinical settings. 

  • Evaluation and validation 

  • Identify methods for evaluating the performance and safety of AI models in radiology. 

Course Directors

William W. Boonn, MD

William Boonn, MD, is the chief medical officer at Rad AI, Inc. He is also a practicing cardiovascular radiologist at the University of Pennsylvania and co-founder and CEO at Equium Intelligence, Inc. prior to its acquisition by Rad AI.

Nina E. Kottler, MD, MS

Nina E. Kottler, MD, MS, has been a practicing radiologist specializing in emergency imaging for more than 17 years. Combining her clinical radiology experience with a graduate degree in applied mathematics, she has been using technologic innovation to drive value in the radiology field.

Ryan K. Lee, MD, MBA

Ryan K. Lee, MD, MBA, is the chair of radiology at the Einstein Healthcare Network and a professor at the Sidney Kimmel College of Medicine at Thomas Jefferson University.


Lisa M. Baumhardt, BSc, MS

Lisa Baumhardt, BSc, MS, is the senior medical device regulatory expert at Hyman, Phelps & McNamara PC. Ms. Baumhardt provides consulting services to medical device, in vitro diagnostic (IVD) and combination product manufacturers.

Tessa S. Cook, MD, PhD

Tessa Cook, MD, PhD, is an associate professor of radiology at the Perelman School of Medicine at the University of Pennsylvania in Philadelphia, where she is also vice chair of practice transformation in the Department of Radiology, the director of the imaging informatics fellowship and modality chief of 3D and advanced imaging.

R. Kent Hutson, MD, CPE

R. Kent Hutson, MD, CPE, has extensive experience in the field of radiology and imaging.

Linda Moy, MD

Linda Moy, MD, is a professor of radiology at the NYU Grossman School of Medicine with additional appointments at the NYU Center for Advanced Imaging Innovation and Research and the NYU Vilcek Institute of Graduate Biomedical Sciences.

Jason Poff, MD

Jason Poff, MD, has been a private practice radiologist at Greensboro Radiology in Greensboro, North Carolina since 2016, where he serves on the local practice board.


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