Encrypted | Login

2021 AAPM Virtual 63rd Annual Meeting - Session: Artificial Intelligence in Treatment Planning and Delivery Q & A

This video is currently visible only to AAPM Members, Affiliates and Developing Country Educational Associates. Embargo periods are typically one year from the date the presentation was first published.

Q & A

When you have finished the video, you may watch again, browse/search all videos, go back to the previous page, or watch another video in this session (see below). add this video to a playlist.

All videos in this session:
Curbing the Errors From Automated Tools Based On An FMEA of An AI-Based Treatment Planning System - Kelly Nealon, MS The University Of Texas MD Anderson Cancer Center
Generalizability Study of a Fluence Map Prediction Network - Lin Ma University of Texas Southwestern Medical Center
Inverse Treatment Planning Using a Virtual Treatment Planner (VTP) for Prostate Cancer Treated with Intensity Modulated Radiation Therapy - Damon Sprouts, MS
Predicting Daily Record of Machine Performance Check Using Multi-Long Short-Term Memory Neural Networks - Min Ma National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College
Towards Automatic Metastasis-Directed Therapy Planning in a Three-Dimensional Beam Model Using Reinforcement Learning - William Hrinivich, PhD Johns Hopkins University School of Medicine
Towards Interpretable Intelligent Automatic Treatment Planning in Radiotherapy: Understanding the Decision-Making Behaviors of a Hierarchical Deep Reinforcement Learning Based Virtual Treatment Planner Network - Chenyang Shen, PhD University of Texas Southwestern Medical Center
Treatment Parameters That Impact IROC SRS Phantom Performance Evaluated Using AI - Hunter Mehrens UT MD Anderson Cancer Center
Graph includes member loads and non-member loads (0 total loads). Exclude non-member? A load is defined as someone coming to this page, not necesarily that they pressed play, or watched the entire presentation.