تقرير
A Dataset for N-ary Relation Extraction of Drug Combinations
| العنوان: | A Dataset for N-ary Relation Extraction of Drug Combinations |
|---|---|
| المؤلفون: | Tiktinsky, Aryeh, Viswanathan, Vijay, Niezni, Danna, Azagury, Dana Meron, Shamay, Yosi, Taub-Tabib, Hillel, Hope, Tom, Goldberg, Yoav |
| سنة النشر: | 2022 |
| المجموعة: | Computer Science |
| مصطلحات موضوعية: | Computer Science - Computation and Language, Computer Science - Information Retrieval |
| الوصف: | Combination therapies have become the standard of care for diseases such as cancer, tuberculosis, malaria and HIV. However, the combinatorial set of available multi-drug treatments creates a challenge in identifying effective combination therapies available in a situation. To assist medical professionals in identifying beneficial drug-combinations, we construct an expert-annotated dataset for extracting information about the efficacy of drug combinations from the scientific literature. Beyond its practical utility, the dataset also presents a unique NLP challenge, as the first relation extraction dataset consisting of variable-length relations. Furthermore, the relations in this dataset predominantly require language understanding beyond the sentence level, adding to the challenge of this task. We provide a promising baseline model and identify clear areas for further improvement. We release our dataset, code, and baseline models publicly to encourage the NLP community to participate in this task. Comment: To appear in NAACL 2022 |
| نوع الوثيقة: | Working Paper |
| URL الوصول: | http://arxiv.org/abs/2205.02289 |
| رقم الأكسشن: | edsarx.2205.02289 |
| قاعدة البيانات: | arXiv |
| الوصف غير متاح. |