Abstract
This paper describes neural models developed for the Social Media Mining for Health (SMM4H) 2020 shared tasks. Specifically, we participated in two tasks. We investigate the use of a language representation model BERT pretrained on a large-scale corpus of 5 million health-related user reviews in English and Russian. The ensemble of neural networks for extraction and normalization of adverse drug reactions ranked first among 7 teams at the SMM4H 2020 Task 3 and obtained a relaxed F1 of 46%. The BERT-based multilingual model for classification of English and Russian tweets that report adverse reactions ranked second among 16 and 7 teams at two first subtasks of the SMM4H 2019 Task 2 and obtained a relaxed F1 of 58% on English tweets and 51% on Russian tweets.- Anthology ID:
- 2020.smm4h-1.8
- Volume:
- Proceedings of the Fifth Social Media Mining for Health Applications Workshop & Shared Task
- Month:
- December
- Year:
- 2020
- Address:
- Barcelona, Spain (Online)
- Editors:
- Graciela Gonzalez-Hernandez, Ari Z. Klein, Ivan Flores, Davy Weissenbacher, Arjun Magge, Karen O'Connor, Abeed Sarker, Anne-Lyse Minard, Elena Tutubalina, Zulfat Miftahutdinov, Ilseyar Alimova
- Venue:
- SMM4H
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 51–56
- Language:
- URL:
- https://aclanthology.org/2020.smm4h-1.8
- DOI:
- Cite (ACL):
- Zulfat Miftahutdinov, Andrey Sakhovskiy, and Elena Tutubalina. 2020. KFU NLP Team at SMM4H 2020 Tasks: Cross-lingual Transfer Learning with Pretrained Language Models for Drug Reactions. In Proceedings of the Fifth Social Media Mining for Health Applications Workshop & Shared Task, pages 51–56, Barcelona, Spain (Online). Association for Computational Linguistics.
- Cite (Informal):
- KFU NLP Team at SMM4H 2020 Tasks: Cross-lingual Transfer Learning with Pretrained Language Models for Drug Reactions (Miftahutdinov et al., SMM4H 2020)
- PDF:
- https://preview.aclanthology.org/improve-issue-templates/2020.smm4h-1.8.pdf
- Code
- andoree/smm4h_classification