International 08 - ASTRO/CSCO Joint Session: AI-Enabled Radiation Therapy for Global Oncology: Practical Implementation for Cost Reduction
MODERATOR(S)
Meng Welliver, MD, PhD - Mayo Clinic Alix School of Medicine
session DESCRIPTION
We will describe high-impact use cases of AI across the radiotherapy workflow, including deciphering EMR, analyzing imaging, generate automated contouring, planning or QA, and generating outcome modeling, with specific relevance to global practice. We will compare AI deployment models suitable for lower-resource environments (cloud vs. on-premise vs. hybrid; centralized planning hubs vs. site-based automation) and their tradeoffs for cost, workforce needs and reliability. We will identify key barriers and enabling infrastructure for safe AI adoption in LMIC radiotherapy programs, including data quality, IT systems, connectivity, cybersecurity and human factors. In addition, we will evaluate equity considerations — how to avoid "AI widening the gap" — including dataset bias, model drift and strategies for inclusive multicenter data collaboration and governance.
learning objectives
- Know available AI options in health care and recognize the difference worldwide.
- Obtain basic understanding and know the steps to acquire AI solutions to bridge the gap based on resources available.
Credits
| AMA PRA Category 1 Credits: | 1.00 |
Presentations
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05:00pm - 05:02pm ETSpeaker: Meng Welliver, MD, PhD - Mayo Clinic Alix School of Medicine, Rochester
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05:02pm - 05:17pm ETSpeaker: Jinming Yu, MD, PhD - Shandong Cancer Hospital, Jinan Shandong
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05:17pm - 05:32pm ETSpeaker: Meng Welliver, MD, PhD - Mayo Clinic Alix School of Medicine, Rochester
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05:32pm - 05:47pm ETSpeaker: Ligang Xing, MD, PhD - Shandong Cancer Hospital, Jinan
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05:47pm - 06:00pm ETSpeaker: Meng Welliver, MD, PhD - Mayo Clinic Alix School of Medicine, Rochester