Papers by Stefan Hegselmann
Large language models are few-shot clinical information extractors (2022.emnlp-main)
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| Challenge: | a long-running goal of clinical NLP is the extraction of important variables trapped in clinical notes. |
| Approach: | They propose to use large language models to tackle diverse clinical extraction tasks . they propose to reannote existing CASI datasets to compare their models with clinical text. |
| Outcome: | The proposed models outperform existing models on few-shot clinical information extraction tasks. |