This repository contains code implementation of experiments in the paper Inferring cancer disease response from radiology reports using large language models with data augmentation and prompting. [JAMIA]
Refer to instructions and training scripts in permutation_contrast folder.
Refer to instructions and training scripts in prompt_based_finetuning folder.
If you find the source code from this work helpful, please cite:
@article{10.1093/jamia/ocad133,
author = {Tan, Ryan Shea Ying Cong and Lin, Qian and Low, Guat Hwa and Lin, Ruixi and Goh, Tzer Chew and Chang, Christopher Chu En and Lee, Fung Fung and Chan, Wei Yin and Tan, Wei Chong and Tey, Han Jieh and Leong, Fun Loon and Tan, Hong Qi and Nei, Wen Long and Chay, Wen Yee and Tai, David Wai Meng and Lai, Gillianne Geet Yi and Cheng, Lionel Tim-Ee and Wong, Fuh Yong and Chua, Matthew Chin Heng and Chua, Melvin Lee Kiang and Tan, Daniel Shao Weng and Thng, Choon Hua and Tan, Iain Bee Huat and Ng, Hwee Tou},
title = "{Inferring cancer disease response from radiology reports using large language models with data augmentation and prompting}",
journal = {Journal of the American Medical Informatics Association},
volume = {30},
number = {10},
pages = {1657-1664},
year = {2023},
month = {07},
issn = {1527-974X},
doi = {10.1093/jamia/ocad133},
url = {https://doi.org/10.1093/jamia/ocad133},
}