Future Directions: AI and Beyond
Includes a Live Web Event on 04/26/2026 at 4:00 PM (EDT)
Future Directions: AI and Beyond
Sunday, April 26, 2026, 4:00pm - 5:00pm Eastern Time (NY/USA)
Description and Objectives
This session will introduce DXA technologists to emerging innovations that are shaping the future of bone densitometry, with an emphasis on artificial intelligence–enabled tools and data integration. Participants will examine how AI-driven quality-control processes and automated region-of-interest detection can enhance measurement consistency, workflow efficiency, and scalability across clinical settings. The program will also examine how DXA data can be linked with large clinical and research datasets to support advanced risk prediction, longitudinal monitoring, and population-level analysis. In addition, participants will discuss key research opportunities and critical knowledge gaps that must be addressed to advance next-generation DXA technologies and inform the evolving role of the DXA technologist.
After attending this lecture, participants will be able to:
- Recognize how AI-enabled quality control and automated region-of-interest detection can improve consistency, efficiency, and scalability of DXA measurements.
- Understand how DXA data can be linked with large clinical and research datasets to support risk prediction, longitudinal monitoring, and population-level analysis.
- Identify key research opportunities and critical gaps that must be addressed to advance the next generation of bone densitometry.
Handouts
All speakers are requested to provide handouts/lecture slides for registered attendees. Those that are provided for this session will be uploaded to the handouts tab and can be accessed/downloaded from that tab.
John A. Shepherd, PhD, FAAPM, CCD
Professor/Chief Scientific Officer
University of Hawaii Cancer Center, Honolulu, HI
Dr. Shepherd is a Researcher/Professor at the University of Hawaii Cancer Center, a Fulbright Scholar, a Fellow of the American Institute for Medical and Biological Engineering (AIMBE), and a former President of the International Society for Clinical Densitometry. He received his PhD in Engineering Physics from the University of Virginia and then completed a Postdoctoral Fellowship in Biophysics at Princeton University. From there he went on to develop body composition and bone density algorithms for a major women’s health company and his patents are the basis for the accuracy of that company’s body composition algorithms. He then joined the Radiology Department of the University of California San Francisco and led his own research group for 19 years studying a wide variety of biomarkers for breast cancer, obesity and osteoporosis from medical imaging using advanced machine learning techniques. For the past 5 years, he has been with the University of Hawaii Cancer Center and is currently their Chief Scientific Officer. He also directs the UH Artificial Intelligence Precision Health Institute and the Hawaii Pacific Islands Mammography Registry. He has been continuously funded from the NIH since 2005, led 6 R01-funded studies, published over 350 peer-review publications that have been referenced over 23,000 times, and lastly is an avid surfer and island ridge hiker!
ASRT Credit
This session is approved by ASRT for 1.00 Category A credits.