Gilbert W. Beebe Symposium: AI and ML Applications in Radiation Therapy, Medical Diagnostics, and Radiation Occupational Health and Safety (2025)
Chapter: Appendix A: Symposium Agenda
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Appendix A
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Suggested Citation:
"Appendix A: Symposium Agenda." National Academies of Sciences, Engineering, and Medicine. 2025. Gilbert W. Beebe Symposium: AI and ML Applications in Radiation Therapy, Medical Diagnostics, and Radiation Occupational Health and Safety. Washington, DC: The National Academies Press.
doi: 10.17226/29200.
Appendix A
Symposium Agenda
PROGRAM
The symposium will include a community discussion on algorithm development and pathways to success, a focus on future directions and opportunities in AI/ML methods and technology to advance the fields of the radiation health sciences, and discussions on the intentionality of data collection for algorithm development and training, as well as focused breakout sessions on current and emerging applications of AI and ML in the radiation health science fields. Sessions will consider such topics as Broader AI Community Discussions, Future Directions and Opportunities for AI/ML Applications in the Radiation Health Sciences, Data for AI Readiness, AI in the Clinic—Applications in Radiation Oncology and Medical Diagnostics, AI Applications in Occupational and Public Health, and AI Regulations and Ethics.
DAY 1 | THURSDAY, MARCH 13, 2025 (All times are U.S. Eastern)
| 8:00 AM | Call to Order and Welcome |
| Charles D. Ferguson, National Academies of Sciences, Engineering, and Medicine Session One | Broader AI Community Discussions |
This session aims to engage thought leaders in the broader AI community to share insights from AI developers, users, and government regulators on balancing the benefits of rapid AI innovation and the risks. Talks will address key responsible AI principles in AI model development, human decision making in AI, ethical considerations, and acceptable uncertainty levels for model outputs.
| Session Introduction and Overview | |
| Co-moderated by Leo Chiang, Co-Chair, The Dow Chemical Company | |
| Co-moderated by Shaheen Dewji, Co-Chair, Georgia Institute of Technology | |
| 8:05 AM | Transformational AI Opportunities in Healthcare |
| David C. Rhew, Microsoft |
Suggested Citation:
"Appendix A: Symposium Agenda." National Academies of Sciences, Engineering, and Medicine. 2025. Gilbert W. Beebe Symposium: AI and ML Applications in Radiation Therapy, Medical Diagnostics, and Radiation Occupational Health and Safety. Washington, DC: The National Academies Press.
doi: 10.17226/29200.
| 8:35 AM | The Journey to Safe and Effective AI Adoption |
| Mike Tilkin, American College of Radiology | |
| 9:05 AM | Session One | Panel Discussion |
| 9:45 AM | BREAK (10 minutes) |
Session Two | Future Directions and Opportunities
This session will explore AI’s primary focus areas within each subfield, covering current practices, emerging developments, and challenges to advancing applications. Presenters will discuss both model development and strategic pathways for implementing AI across radiation therapy, diagnostics, occupational health, and environmental safety. The session will emphasize human oversight, ethical considerations, and responsible AI integration to support effective, reliable decision making in these diverse fields.
Session Two A | Future Directions and Opportunities
| 9:55 AM | Session Introduction and Overview | Radiation Therapy/Oncology |
| Co-moderated by Anyi Li, Planning Committee, Memorial Sloan Kettering Cancer Center | |
| Co-moderated by Ceferino Obcemea, Planning Committee, National Cancer Institute | |
| 10:00 AM | AI Agents for Adaptive Radiotherapy |
| Steve Jiang, University of Texas Southwestern | |
| 10:15 AM | Multi-omics Integration and Pattern Discovery in Patient Data Using Spatially |
| Semantic Topographic Maps | |
| Lei Xing, Stanford University | |
| 10:30 AM | Session Two A | Panel Discussion |
| Session Two B | Future Directions and Opportunities | |
| 11:10 AM | Session Introduction and Overview | Medical Diagnostics |
| Moderated by Caroline Chung, Planning Committee, MD Anderson Cancer Center | |
| 11:15 AM | Quantitative MR, Promising Data as a Replacement of CT |
| Cameron Piron, Synaptive Medical | |
| 11:30 AM | AI and Quantitative Imaging |
| Jayashree Kalpathy-Cramer, University of Colorado-Anschutz Medical Campus | |
| 11:45 AM | Session Two B | Panel Discussion |
| 12:25 PM | LUNCH (1 hour) |
Suggested Citation:
"Appendix A: Symposium Agenda." National Academies of Sciences, Engineering, and Medicine. 2025. Gilbert W. Beebe Symposium: AI and ML Applications in Radiation Therapy, Medical Diagnostics, and Radiation Occupational Health and Safety. Washington, DC: The National Academies Press.
doi: 10.17226/29200.
Session Two C | Future Directions and Opportunities
| 1:25 PM | Session Introduction and Overview | AI/ML Innovations in Radiation Occupational Health |
| Moderated by Sylvain Costes, Planning Committee, NASA | |
| 1:30 PM | Computational Approaches to Assessing Radiation Exposure Across the Life Course: Risks, Insights, and Innovations |
| Heidi Hanson, Oak Ridge National Laboratory | |
| 1:45 PM | Patient-Centric Synthetic Data Generation, No Reason to Risk Re-identification in Biomedical Data Analysis: The Anonymous Synthetic Data Era |
| Pierre-Antoine Gourraud, Nantes Université, University Medical Center (CHU de Nantes), France | |
| 2:00 PM | Session Two C | Panel Discussion |
| 2:40 PM | BREAK (10 minutes) |
Session Three | Data for AI Readiness
This session will explore the significance of intentional data collection for trustworthy AI model results with a focus on medical imaging as an example. Key topics include data quality and quantity requirements, data collection planning, and data management strategies. Discussion will focus on tackling major gaps, bias, and ethical considerations in radiation health sciences data while suggesting innovative solutions.
| 2:50 PM | Session Introduction and Overview |
| Co-moderated by Leo Chiang, Co-Chair, The Dow Chemical Company | |
| Co-moderated by Anyi Li, Planning Committee, Memorial Sloan Kettering Cancer Center | |
| 2:55 PM | Data for AI: The Critical Role of Metadata and Context |
| Caroline Chung, MD Anderson Cancer Center | |
| 3:10 PM | Requisites and Challenges in Quantitative Imaging |
| Daniel C. Sullivan, Duke University Medical Center | |
| 3:25 PM | Centralized Imaging Collaborations for AI Readiness |
| Paul Kinahan, University of Washington | |
| 3:40 PM | Data Management Tools and Strategy for Responsible Imaging AI |
| Daniel Marcus, Washington University School of Medicine in St. Louis | |
| 3:55 PM | Session Three | Panel Discussion |
| 4:05 PM | BREAK (10 minutes) |
Suggested Citation:
"Appendix A: Symposium Agenda." National Academies of Sciences, Engineering, and Medicine. 2025. Gilbert W. Beebe Symposium: AI and ML Applications in Radiation Therapy, Medical Diagnostics, and Radiation Occupational Health and Safety. Washington, DC: The National Academies Press.
doi: 10.17226/29200.
Session Four | Community Discussion and End-of-Day Notes
| 4:15 PM | Radiation Therapy Wrap-up |
| Report from Anyi Li | |
| 4:25 PM | Medical Diagnostics Wrap-up |
| Report from Caroline Chung | |
| 4:35 PM | Exposure Assessment Wrap-up |
| Report from Sylvain Costes | |
| 4:45 PM | End of Day, Closing Remarks, and Summary on Common Themes |
| Shaheen Dewji | |
| 5:00 PM | Adjourn | End of Day 1 of Symposium |
Day 2 will provide a platform for invited speakers and participants to present and discuss advancements in AI and ML across diverse areas of radiation science, including health, occupational safety, environmental monitoring, and regulatory frameworks. Moderated panel sessions will build on insights from Day 1’s “Future Directions and Opportunities” session, advancing discussions on the application, ethical considerations, and governance of AI across multiple radiation-related fields. This day’s agenda will support a comprehensive exploration of AI’s role in enhancing radiation safety, data integration, and regulatory processes, fostering collaboration among experts from varied domains within radiation science.
DAY 2 | FRIDAY, MARCH 14, 2025 (All times are U.S. Eastern.)
| 8:00 AM | Welcome and Overview for Day 2 |
| Leo Chiang, Co-Chair, The Dow Chemical Company | |
| Shaheen Dewji, Co-Chair, Georgia Institute of Technology | |
| Session Five | Breakout Sessions Five A and Five B |
Breakout Session Five A | Location—Fred Kavli Auditorium
| 8:05 AM | Session Five A | Digital Twins |
| Session Introduction and Overview | |
| Co-moderated by Caroline Chung, Planning Committee, MD Anderson Cancer Center | |
| Co-moderated by Sylvain Costes, Planning Committee, NASA | |
| 8:15 AM | Cardiac Digital Twins: From the Academy to the Clinic |
| Charles A. Taylor, University of Texas at Austin | |
| 8:40 AM | Digital Twins for Disease Modeling and Drug Development |
| Jon Walsh, Unlearn | |
Suggested Citation:
"Appendix A: Symposium Agenda." National Academies of Sciences, Engineering, and Medicine. 2025. Gilbert W. Beebe Symposium: AI and ML Applications in Radiation Therapy, Medical Diagnostics, and Radiation Occupational Health and Safety. Washington, DC: The National Academies Press.
doi: 10.17226/29200.
| 9:05 AM | Multiscale Digital Twins for Personalized Radiopharmaceutical Therapy |
| Greeshma Agasthya, Georgia Institute of Technology | |
| 9:30 AM | DT and AI for Precision Medicine |
| Jun Deng, Yale University | |
| 9:55 AM | Session Five A | Panel Discussion |
| 11:00 AM | LUNCH (1 hour) |
Breakout Session Five B | Location—NAS 120
| 8:05 AM | Session Five B | AI/ML Applications of Multimodal Modeling |
| Session Introduction and Overview | |
| Co-moderated by Anyi Li, Planning Committee, Memorial Sloan Kettering Cancer Center | |
| Co-moderated by Ceferino Obcemea, Planning Committee, National Cancer Institute | |
| 8:15 AM | Integrating Mechanistic Modeling with Machine Learning to Evaluate Radiotherapy and Chemotherapy Outcomes in Head and Neck Cancer |
| Igor Shuryak, Columbia University Irving Medical Center (CUIMC) | |
| 8:40 AM | Rapidly Exploring Use Cases for Multimodal AI in Radiology |
| Nur Yildirim, University of Virginia | |
| 9:05 AM | Understanding Radiation Risk Through Deep Learning: Promise and Challenges |
| Zhenqiu Liu, Radiation Effects Research Foundation (RERF), Japan | |
| 9:30 AM | AI and Multimodal Modeling in Lung Cancer |
| Jia Wu, MD Anderson Cancer Center | |
| 9:55 AM | Session Five B | Panel Discussion |
| 11:00 AM | LUNCH (1 hour) |
Session Six | Breakout Sessions Six A and Six B
Breakout Session Six A | Location—Fred Kavli Auditorium
| 12:00 PM | Session Six A | Ethics and Bias |
| Session Introduction and Overview | |
| Moderated by Leo Chiang, Co-Chair, The Dow Chemical Company | |
| 12:00 PM | Artificial Intelligence Preparedness—A Regulatory Perspective |
| Matt Dennis, U.S. Nuclear Regulatory Commission |
Suggested Citation:
"Appendix A: Symposium Agenda." National Academies of Sciences, Engineering, and Medicine. 2025. Gilbert W. Beebe Symposium: AI and ML Applications in Radiation Therapy, Medical Diagnostics, and Radiation Occupational Health and Safety. Washington, DC: The National Academies Press.
doi: 10.17226/29200.
| 12:25 PM | Issues in the Use of AI for Breast Cancer Screening |
| Etta D. Pisano, American College of Radiology | |
| 12:50 PM | Addressing Bias in AI-Driven Medical Imaging: Pitfalls and Best Practices |
| Amber Simpson, Queen’s University, Canada | |
| 1:15 PM | Shortcuts Causing Bias in Medical Imaging |
| Judy Wawira Gichoya, Emory University School of Medicine | |
| 1:40 PM | Session Six A | Panel Discussion |
| 2:40 PM | BREAK (20 minutes) |
Breakout Session Six B | Location—NAS 120
| 12:00 PM | Session Six B | Uncertainty Quantification and Trustworthiness |
| Session Introduction and Overview | |
| Co-moderated by Shaheen Dewji, Co-Chair, Georgia Institute of Technology | |
| Co-moderated by Ceferino Obcemea, Planning Committee, National Cancer Institute | |
| 12:00 PM | Assessing Uncertainty in Indoor Radon Exposure Estimates: Implications for Radiation Epidemiology |
| Heidi Hanson, Oak Ridge National Laboratory | |
| 12:25 PM | Enhancing Trustworthiness: A Case Study on Blood Pressure Modeling with Physics-Informed Neural Networks |
| Roozbeh Jafari, Massachusetts Institute of Technology Lincoln Laboratory | |
| 12:50 PM | Jie Yu, Johnson & Johnson |
| 1:15 PM | Machine Learning and Low-Field MRI: Unlocking a New Class of Portable Scanners |
| Matthew Rosen, Harvard Medical School | |
| 1:40 PM | Session Six B | Panel Discussion |
| 2:40 PM | BREAK (20 minutes) |
| 3:00 PM | Summary of Symposium and Highlight Discussions |
| Leo Chiang, Co-Chair | |
| Shaheen Dewji, Co-Chair | |
| Daniel Mulrow, National Academies Symposium Director | |
| 3:15 PM | Adjourn Symposium | End of Day 2 Symposium |
Suggested Citation:
"Appendix A: Symposium Agenda." National Academies of Sciences, Engineering, and Medicine. 2025. Gilbert W. Beebe Symposium: AI and ML Applications in Radiation Therapy, Medical Diagnostics, and Radiation Occupational Health and Safety. Washington, DC: The National Academies Press.
doi: 10.17226/29200.
Suggested Citation:
"Appendix A: Symposium Agenda." National Academies of Sciences, Engineering, and Medicine. 2025. Gilbert W. Beebe Symposium: AI and ML Applications in Radiation Therapy, Medical Diagnostics, and Radiation Occupational Health and Safety. Washington, DC: The National Academies Press.
doi: 10.17226/29200.
Suggested Citation:
"Appendix A: Symposium Agenda." National Academies of Sciences, Engineering, and Medicine. 2025. Gilbert W. Beebe Symposium: AI and ML Applications in Radiation Therapy, Medical Diagnostics, and Radiation Occupational Health and Safety. Washington, DC: The National Academies Press.
doi: 10.17226/29200.
Suggested Citation:
"Appendix A: Symposium Agenda." National Academies of Sciences, Engineering, and Medicine. 2025. Gilbert W. Beebe Symposium: AI and ML Applications in Radiation Therapy, Medical Diagnostics, and Radiation Occupational Health and Safety. Washington, DC: The National Academies Press.
doi: 10.17226/29200.
Suggested Citation:
"Appendix A: Symposium Agenda." National Academies of Sciences, Engineering, and Medicine. 2025. Gilbert W. Beebe Symposium: AI and ML Applications in Radiation Therapy, Medical Diagnostics, and Radiation Occupational Health and Safety. Washington, DC: The National Academies Press.
doi: 10.17226/29200.
Suggested Citation:
"Appendix A: Symposium Agenda." National Academies of Sciences, Engineering, and Medicine. 2025. Gilbert W. Beebe Symposium: AI and ML Applications in Radiation Therapy, Medical Diagnostics, and Radiation Occupational Health and Safety. Washington, DC: The National Academies Press.
doi: 10.17226/29200.
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