3 accepted papers
In-hospital text data contains valuable clinical information, yet deploying fine-tuned small language models (SLMs) for information extraction remains challenging due to differences in formatting and vocabulary across institutions. Since access to the original in-hospital data (source domain) is oft…
The scarcity of publicly available clinical corpora hinders developing and applying NLP tools in clinical research. While existing work tackles this issue by utilizing generative models to create high-quality synthetic corpora, their methods require learning from the original in-hospital clinical do…
Temporal relation annotation in the clinical domain is crucial yet challenging due to its workload and the medical expertise required. In this paper, we propose a novel annotation method that integrates event start-points ordering and question-answering (QA) as the annotation format. By focusing onl…