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)
Venue:
SMM4H
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
46–50
Language:
URL:
https://aclanthology.org/2020.smm4h-1.7
DOI:
Bibkey:
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)
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PDF:
https://aclanthology.org/2020.smm4h-1.7.pdf