1 code implementation • 19 Jan 2024 • Zhengliang Liu, Jason Holmes, Wenxiong Liao, Chenbin Liu, Lian Zhang, Hongying Feng, Peilong Wang, Muhammad Ali Elahi, Hongmin Cai, Lichao Sun, Quanzheng Li, Xiang Li, Tianming Liu, Jiajian Shen, Wei Liu
ROND is specifically designed to address this gap in the domain of radiation oncology, a field that offers many opportunities for NLP exploration.
no code implementations • 2 Dec 2023 • Lian Zhang, Jason M. Holmes, Zhengliang Liu, Hongying Feng, Terence T. Sio, Carlos E. Vargas, Sameer R. Keole, Kristin Stützer, Sheng Li, Tianming Liu, Jiajian Shen, William W. Wong, Sujay A. Vora, Wei Liu
The noisy probing dose method showed better generalizability in the 6 outlier cases than the ROI-based and beam mask-based methods with 3D Gamma passing rates (for prostate cancer, targets: 89. 32%$\pm$1. 45% vs. 93. 48%$\pm$1. 51% vs. 96. 79%$\pm$0. 83%, OARs: 85. 87%$\pm$1. 73% vs. 91. 15%$\pm$1. 13% vs. 94. 29%$\pm$1. 01%).
no code implementations • 1 Apr 2023 • Jason Holmes, Zhengliang Liu, Lian Zhang, Yuzhen Ding, Terence T. Sio, Lisa A. McGee, Jonathan B. Ashman, Xiang Li, Tianming Liu, Jiajian Shen, Wei Liu
We present the first study to investigate Large Language Models (LLMs) in answering radiation oncology physics questions.