A Dual-Attention Network for Joint Named Entity Recognition and Sentence Classification of Adverse Drug Events
Susmitha Wunnava, Xiao Qin, Tabassum Kakar, Xiangnan Kong, Elke Rundensteiner
Abstract
An adverse drug event (ADE) is an injury resulting from medical intervention related to a drug. Automatic ADE detection from text is either fine-grained (ADE entity recognition) or coarse-grained (ADE assertive sentence classification), with limited efforts leveraging inter-dependencies among the two granularities. We instead propose a multi-grained joint deep network to concurrently learn the ADE entity recognition and ADE sentence classification tasks. Our joint approach takes advantage of their symbiotic relationship, with a transfer of knowledge between the two levels of granularity. Our dual-attention mechanism constructs multiple distinct representations of a sentence that capture both task-specific and semantic information in the sentence, providing stronger emphasis on the key elements essential for sentence classification. Our model improves state-of- art F1-score for both tasks: (i) entity recognition of ADE words (12.5% increase) and (ii) ADE sentence classification (13.6% increase) on MADE 1.0 benchmark of EHR notes.- Anthology ID:
- 2020.findings-emnlp.306
- Volume:
- Findings of the Association for Computational Linguistics: EMNLP 2020
- Month:
- November
- Year:
- 2020
- Address:
- Online
- Venue:
- Findings
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 3414–3423
- Language:
- URL:
- https://aclanthology.org/2020.findings-emnlp.306
- DOI:
- 10.18653/v1/2020.findings-emnlp.306
- Cite (ACL):
- Susmitha Wunnava, Xiao Qin, Tabassum Kakar, Xiangnan Kong, and Elke Rundensteiner. 2020. A Dual-Attention Network for Joint Named Entity Recognition and Sentence Classification of Adverse Drug Events. In Findings of the Association for Computational Linguistics: EMNLP 2020, pages 3414–3423, Online. Association for Computational Linguistics.
- Cite (Informal):
- A Dual-Attention Network for Joint Named Entity Recognition and Sentence Classification of Adverse Drug Events (Wunnava et al., Findings 2020)
- PDF:
- https://preview.aclanthology.org/auto-file-uploads/2020.findings-emnlp.306.pdf