October 24 Oct 24
2023
12:00 PM - 01:00 PM
Tuesday Tue

Location

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Stanford University School of Medicine

291 Campus Dr
Stanford, CA 94305
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Event

Medical Physics Seminar - Eric Ford

The ART of Quality: Ensuring quality of care in the era of Adaptive Radiation Therapy and AI

Time:
12:00pm – 1:00pm Seminar & Discussion

Location:
Zoom Webinar

Webinar Registration:
https://stanford.zoom.us/webinar/register/WN_Y5QwpIWMQ3ugvdnzT_iyEQ

Check your email for the Zoom webinar link after you have registered

Speaker

Eric Ford, PhD, Professor, Director, and Vice-Chair of Medical Physics at the University of Washington 

Dr. Ford is Professor, Director, and Vice-Chair of Medical Physics at the University of Washington in Seattle where he oversees the physics services of a department treating approximately 3000 patients per year with advanced technologies such as adaptive radiation therapy and proton therapy. His areas of expertise are quality and safety, development of laboratory technology for experimental radiobiology, and global oncology. He has published over 160 papers, three books and has been the Principal Investigator of multiple federal grants. His is an active member of American Association of Physicists in Medicine (AAPM) and the American Society for Radiation Oncology (ASTRO) and currently serves on the ASTRO Board of Directors. He is a valued mentor to students, residents and postdoctoral research. He is the author of the widely-used textbook “Primer on Radiation Oncology Physics: Video Tutorials with Textbook and Problems” and has been recognized with five teaching awards.

Abstract

Radiation therapy is undergoing a time of rapid proliferation of technology and techniques, coupled with an increasing will to improve access and reduce healthcare disparities. At the same time a quality gap exists in outcomes for patients receiving RT. In this presentation we will explore what is known about the quality gap with a special focus on Adaptive Radiation Therapy (ART). Tools are emerging to address this gap, many of them powered by techniques in machine learning or artificial intelligence (AI). Potential future improvements will rely on our ability to understand and apply these tools.