Optimization of uncomplicated control for head and neck tumors.

By A. Ågren, Anders Brahme, I. Turesson. 1990

Citations in the corpus

• Deep Reinforcement Learning for Automated Radiation Adaptation in Lung Cancer (2017, neutral): “Let A = {a1 = dose/frac} ⊆ R be the allowed actions after t = t∗ and define our reward function R(s, a) = R(s) based on the complication-free tumor control (P+) utility [25] while respecting the dose escalation clinical protocol requirement:”
• Normal tissue reactions to radiotherapy (2009, unknown): “However, although there is some evidence for a lin”