Author

Kenneth E. Rosenzweig

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Open access Sep 2026

Improving portability of knowledge‐based planning using an LLM‐driven plan refinement framework in lung radiotherapy

Knowledge‐based planning (KBP) has improved the quality and efficiency of radiotherapy treatment planning. However, its broader clinical adoption remains limited because effective deployment often requires institution‐specific model training and tuning. Publicly available KBP models provide a convenient starting point...

Zi-Pai Wang, Hao Guo, Yang Lei et al. · Medical Physics (Lancaster) · 1 citation

Sep 2026

A Modular Multi-Agent Reinforcement Learning Framework Guided by LLMs: Improving Quality and Efficiency of Treatment Planning in Lung Radiotherapy.

PURPOSE Knowledge-based planning (KBP) frequently requires manual refinement to satisfy institution-specific clinical constraints, while existing automated approaches based on large language models (LLMs) or reinforcement learning (RL) each face distinct limitations in long-term optimization awareness and scalability....

Zi-Pai Wang, Hao Guo, Yang Lei et al. · International Journal of Rad... · 0 citations

#small language model Open access Sep 2026

PlanningCopilot: An agentic framework integrating ESAPI modules for autonomous treatment planning in lung radiotherapy.

PlanCopilot consistently satisfies clinical dosimetric requirements across varying anatomical complexities and improves optimization efficiency through self-learning from prior optimization history.

Hao Guo, Zi-Pai Wang, Tenzin Kunkyab et al. · Medical Physics (Lancaster) · 1 citation