A reinforcement learning agent for head and neck intensity-modulated radiation therapy

A reinforcement learning agent for head and neck intensity-modulated radiation therapy

Head and neck (HN) cancers pose a difficult problem in the planning of intensity-modulated radiation therapy (IMRT) treatment. The primary tumor can be large and asymmetrical, and multiple organs at risk (OARs) with varying dose-sparing goals lie close to the target volume. Currently, there is no sy...

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Bibliographic Details
Main Authors: Hunter Stephens, Xinyi Li, Yang Sheng, Qiuwen Wu, Yaorong Ge, Q. Jackie Wu
Format: Article
Language:English
Published: Frontiers Media S.A. 2024-02-01
Series:Frontiers in Physics
Subjects:
reinforcement learning
radiation therapy
automated treatment planning
head and neck cancer
interpretable machine learning
Online Access:https://www.frontiersin.org/articles/10.3389/fphy.2024.1331849/full

Internet

https://www.frontiersin.org/articles/10.3389/fphy.2024.1331849/full

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