| Autor: |
RICHTER-PECHANSKI, Phillip, WIESENBACH, Philipp, SCHWAB, Dominic M., KIRIAKOU, Christina, Mingyang HE, GEIS, Nicolas A., FRANK, Anette, DIETERICH, Christoph |
| Zdroj: |
Studies in Health Technology & Informatics; 2023, Vol. 302, p819-820, 2p, 1 Chart |
| Abstrakt: |
To classify sentences in cardiovascular German doctor's letters into eleven section categories, we used pattern-exploiting training, a prompt-based method for text classification in few-shot learning scenarios (20, 50 and 100 instances per class) using language models with various pre-training approaches evaluated on CARDIO:DE, a freely available German clinical routine corpus. Prompting improves results by 5-28% accuracy compared to traditional methods, reducing manual annotation efforts and computational costs in a clinical setting. [ABSTRACT FROM AUTHOR] |
| Databáze: |
Complementary Index |
| Externí odkaz: |
|
