The Use of AI in Off Line Adaptive Planning Decision Making

A review of a novel software by TheraPanacea that uses AI and Deep Learning algorithms to help make the offline adaptive planning decision-making process more efficient, streamlined, and standardized. Bringing cutting-edge technology to all radiation oncology patients, not just for ones being treated on online adaptive specialty machines.

Learner Outcomes:
1. Outline the offline adaptive decision-making process
2. Discuss how AI and Deep Learning algorithms are involved in the offline adaptive process
3. Review the use of enhanced CBCTs and synthetic CT generation in offline adaptive processes

CE credit = 0.5

Stephanie Torres, CMD

Technical Sales Specialist

TheraPanacea

Stephanie Torres, CMD has been a medical dosimetrist for 27 years. Now working on the Industry side in Artificial Intelligence and Deep Learning programs. I like to mentor young professionals looking to get into Medical Dosimetry. For fun I travel, design and sew my own wardrobe and enjoy being a grandma!

Components visible upon registration.

REMINDER

CE Deadline Approaching 

All participants need to complete the session quizzes before before 11:59 PM ET on April 4 to earn CE credits.

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