most citedAutomating proton PBS treatment planning for head and neck cancers using policy gradient-based deep reinforcement learning

1 citations · 1 across the 2 of their papers we have counts for

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2 papers

cs.AI2025

A learning-driven automatic planning framework for proton PBS treatments of H&N cancers

Qingqing Wang, Liqiang Xiao, Chang Chang

Proton pencil beam scanning (PBS) treatment planning for head & neck (H&N) cancers involves numerous conflicting objectives, requiring iterative objective parameter adjustments to…

q-bio.QM2024★ 1 cited

Automating proton PBS treatment planning for head and neck cancers using policy gradient-based deep reinforcement learning

Qingqing Wang, Chang Chang

Proton pencil beam scanning (PBS) treatment planning for head and neck (H&N) cancers is a time-consuming and experience-demanding task where a large number of planning objectives a…