@inproceedings{gusev-etal-2020-bert,
title = "{BERT} Implementation for Detecting Adverse Drug Effects Mentions in {R}ussian",
author = "Gusev, Andrey and
Kuznetsova, Anna and
Polyanskaya, Anna and
Yatsishin, Egor",
editor = "Gonzalez-Hernandez, Graciela and
Klein, Ari Z. and
Flores, Ivan and
Weissenbacher, Davy and
Magge, Arjun and
O'Connor, Karen and
Sarker, Abeed and
Minard, Anne-Lyse and
Tutubalina, Elena and
Miftahutdinov, Zulfat and
Alimova, Ilseyar",
booktitle = "Proceedings of the Fifth Social Media Mining for Health Applications Workshop {\&} Shared Task",
month = dec,
year = "2020",
address = "Barcelona, Spain (Online)",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2020.smm4h-1.7",
pages = "46--50",
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.",
}
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<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.</abstract>
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%0 Conference Proceedings
%T BERT Implementation for Detecting Adverse Drug Effects Mentions in Russian
%A Gusev, Andrey
%A Kuznetsova, Anna
%A Polyanskaya, Anna
%A Yatsishin, Egor
%Y Gonzalez-Hernandez, Graciela
%Y Klein, Ari Z.
%Y Flores, Ivan
%Y Weissenbacher, Davy
%Y Magge, Arjun
%Y O’Connor, Karen
%Y Sarker, Abeed
%Y Minard, Anne-Lyse
%Y Tutubalina, Elena
%Y Miftahutdinov, Zulfat
%Y Alimova, Ilseyar
%S Proceedings of the Fifth Social Media Mining for Health Applications Workshop & Shared Task
%D 2020
%8 December
%I Association for Computational Linguistics
%C Barcelona, Spain (Online)
%F gusev-etal-2020-bert
%X 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.
%U https://aclanthology.org/2020.smm4h-1.7
%P 46-50
Markdown (Informal)
[BERT Implementation for Detecting Adverse Drug Effects Mentions in Russian](https://aclanthology.org/2020.smm4h-1.7) (Gusev et al., SMM4H 2020)
ACL