Evaluating Large Language Models on a Highly-specialized Topic, Radiation Oncology Physics. - Jason Holmes; Zhengliang Liu; Lian Zhang; Yuzhen Ding; Terence T. Sio; Lisa A. McGee; Jonathan B. Ashman; Xiang Li 001; Tianming Liu 001; Jiajian Shen; Wei Liu 146 (CoRR, 2023)

Deep-Learning-based Fast and Accurate 3D CT Deformable Image Registration in Lung Cancer. - Yuzhen Ding; Hongying Feng; Yunze Yang; Jason Holmes; Zhengliang Liu; David Liu; William W. Wong; Nathan Y. Yu; Terence T. Sio; Steven E. Schild; Baoxin Li; Wei Liu (CoRR, 2023)

RadOnc-GPT: A Large Language Model for Radiation Oncology. - Zhengliang Liu; Peilong Wang; Yiwei Li 002; Jason Holmes; Peng Shu; Lian Zhang; Chenbin Liu; Ninghao Liu; Dajiang Zhu; Xiang Li 001; Quanzheng Li; Samir H. Patel; et al. (CoRR, 2023)

Noisy probing dose facilitated dose prediction for pencil beam scanning proton therapy: physics enhances generalizability. - Lian Zhang; Jason M. Holmes; Zhengliang Liu; Hongying Feng; Terence T. Sio; Carlos E. Vargas; Sameer R. Keole; Kristin Stützer; Sheng Li 001; Tianming Liu 001; Jiajian Shen; William W. Wong; et al. (CoRR, 2023)

Fine-Tuning Open-Source Large Language Models to Improve Their Performance on Radiation Oncology Tasks: A Feasibility Study to Investigate Their Potential Clinical Applications in Radiation Oncology. - Peilong Wang; Zhengliang Liu; Yiwei Li 002; Jason Holmes; Peng Shu; Lian Zhang; Xiang Li 001; Quanzheng Li; Brady S. Laughlin; Diego Santos Toesca; Sujay A. Vora; Samir H. Patel; et al. (CoRR, 2025)

LLM-Match: An Open-Sourced Patient Matching Model Based on Large Language Models and Retrieval-Augmented Generation. - Xiaodi Li; Shaika Chowdhury; Chung-Il Wi; Maria Vassilaki; Xiaoke Liu; Terence T. Sio; Owen Garrick; Young J. Juhn; James R. Cerhan; Cui Tao; Nansu Zong (CoRR, 2025)