Annapolis, MD / September 9, 2025 – RadSite™, a leading accrediting agency promoting safety and quality in imaging, and Trajectory® Health AI are sponsoring a complimentary webinar entitled “How AI Solutions Are Changing Healthcare.”

The event will take place on Tuesday, September 16, 2025, from 1:00 to 2:00 p.m. EDT. To register, click here.

Moderator/Speaker

  • Rene Quashie, JD, Vice President, Digital Health, Consumer Technology Association, producer of CES®

Speakers

  • Mark Hiatt, MD, MBA, MS, Chief Medical Officer, RadSite
  • Eliot Siegel, MD, Chief Innovation Officer, RadSite
  • Jenifer Siegelman, MD, MPH, Principal, Photo 52 Group
  • Thomas Wilson, PhD, DrPH, Chief Epidemiologist and Co-Founder, Trajectory Health AI

“I am looking forward to moderating this roundtable discussion on how AI is changing the U.S. healthcare delivery system,” notes Rene Quashie, JD, Vice President of Digital Health for the Consumer Technology Association. “As a standard development organization accredited by the American National Standards Institute, the Consumer Technology Association is playing  a leading role in developing AI Standards. We need to develop clear steps to support evidence-based AI applications in medicine.

“Artificial intelligence is beginning to transform imaging and diagnostics—enhancing accuracy, efficiency, and the ability to personalize care,” adds Mark Hiatt, MD, MBA, MS, Chief Medical Officer, RadSite. “ While these advances are exciting, they also raise important questions about quality and oversight. At RadSite, our mission has always been to ensure that new technologies are integrated responsibly into clinical practice, with safety and performance as guiding principles. By applying the same rigorous, standards-based approach we bring to imaging accreditation, we may be able help healthcare embrace AI in ways that protect patients, build trust, and deliver better outcomes.”

The roundtable discussion will examine various types of AI models and their interaction with human intelligence, including pre-generative and generative models, static and dynamic models, large language models, and the data on which they are based (e.g., natural language processing). Participants will debate the implications for clinical care, medical research, future decisions about resource allocation made by insurance companies and health systems, and public and private oversight.