BERT Implementation for Detecting Adverse Drug Effects Mentions in Russian
Andrey Gusev, Anna Kuznetsova, Anna Polyanskaya, Egor Yatsishin
Abstract
This paper describes a system developed for the Social Media Mining for Health 2020 shared task. Our team participated in the second subtask for Russian language creating a system to detect adverse drug reaction presence in a text. For our submission, we exploited an ensemble model architecture, combining BERT’s extension for Russian language, Logistic Regression and domain-specific preprocessing pipeline. Our system was ranked first among others, achieving F-score of 0.51.- Anthology ID:
- 2020.smm4h-1.7
- 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:
- 46–50
- Language:
- URL:
- https://aclanthology.org/2020.smm4h-1.7
- DOI:
- Cite (ACL):
- Andrey Gusev, Anna Kuznetsova, Anna Polyanskaya, and Egor Yatsishin. 2020. BERT Implementation for Detecting Adverse Drug Effects Mentions in Russian. In Proceedings of the Fifth Social Media Mining for Health Applications Workshop & Shared Task, pages 46–50, Barcelona, Spain (Online). Association for Computational Linguistics.
- Cite (Informal):
- BERT Implementation for Detecting Adverse Drug Effects Mentions in Russian (Gusev et al., SMM4H 2020)
- PDF:
- https://preview.aclanthology.org/ingest-acl-2023-videos/2020.smm4h-1.7.pdf