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AI and Machine Learning for RT

S Jiang1*, L Xing2*, I El Naqa3*, H Li4*, (1) UT Southwestern Medical Center, Dallas, TX, (2) Stanford University School of Medicine, Stanford, CA, (3) University of Michigan, Ann Arbor, MI, (4) Washington University School of Medicine, Saint Louis, MO





Presentations

(Thursday, 7/18/2019) 7:30 AM - 9:30 AM

Room: Stars at Night Ballroom 1

The progress of artificial intelligence (AI) technologies has recently been exponential and shown to be both transformative and disruptive in many fields such as computer vision, natural language processing, audio processing, and automobile auto piloting. AI is expected to have a significant impact on healthcare. For radiation oncology, AI may greatly improve the treat outcome and reduce toxicity by providing more precise cancer detection, diagnosis, staging etc, more personalized and precision treatment strategy, more accurate target delineation and organ segmentation, better, faster, and more precise treatment planning and delivery, and more convenient, frequent, and accurate patient follow up. AI may greatly improve patient safety by automatically detecting and preventing medical errors, and through the use of wearable sensors and RTLS technologies. AI may also greatly reduce healthcare disparity by transferring the high quality care from major academic centers to under-served patients via well trained AI software tools. In the session, we will focus on the potential impact of AI on four important aspects of radiation oncology: treatment planning, organ segmentation and target delineation, adaptive therapy, and motion management. We will review the current status of using AI and machine learning, and present our vision on the future development of AI, in those areas.

Learning Objectives:
1. Understand the current status and future direction of AI research for radiotherapy treatment planning;
2. Understand the current status and future direction of AI research for organ segmentation and target delineation for radiotherapy;
3. Understand the current status and future direction of AI research for adaptive radiotherapy;
4. Understand the current status and future direction of AI research for motion management in radiotherapy.

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