1 citations · 1 across the 2 of their papers we have counts for
3 papers
cs.AI2026
An Evidence-Driven Multi-Agent Compound AI System for Head and Neck Proton Radiotherapy Planning
Qingqing Wang, Liqiang Xiao, Chang Chang
Radiation treatment planning requires balancing competing objectives to satisfy clinical criteria while accommodating physicians' preferences. This study aims to develop an evidenc…
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…