Sentence transformers and bayesian optimization for adverse drug effect detection from twitter

O Gencoglu - Proceedings of the Fifth Social Media Mining for …, 2020 - aclanthology.org
This paper describes our approach for detecting adverse drug effect mentions on Twitter as
part of the Social Media Mining for Health Applications (SMM4H) 2020, Shared Task 2. Our …

Detection of adverse drug reaction in tweets using a combination of heterogeneous word embeddings

ST Aroyehun, A Gelbukh - Proceedings of the fourth social media …, 2019 - aclanthology.org
This paper details our approach to the task of detecting reportage of adverse drug reaction
in tweets as part of the 2019 social media mining for healthcare applications shared task …

Autobots Ensemble: Identifying and Extracting Adverse Drug Reaction from Tweets Using Transformer Based Pipelines

S Saha, S Das, P Khurana… - Proceedings of the Fifth …, 2020 - aclanthology.org
This paper details a system designed for Social Media Mining for Health Applications
(SMM4H) Shared Task 2020. We specifically describe the systems designed to solve task 2 …

MIDAS@ SMM4H-2019: identifying adverse drug reactions and personal health experience mentions from twitter

D Mahata, S Anand, H Zhang, S Shahid… - Proceedings of the …, 2019 - aclanthology.org
In this paper, we present our approach and the system description for the Social Media
Mining for Health Applications (SMM4H) Shared Task 1, 2 and 4 (2019). Our main …

Deep learning for identification of adverse effect mentions in twitter data

P Barry, O Uzuner - Proceedings of the Fourth Social Media …, 2019 - aclanthology.org
Abstract Social Media Mining for Health Applications (SMM4H) Adverse Effect Mentions
Shared Task challenges participants to accurately identify spans of text within a tweet that …

Transformer models for drug adverse effects detection from tweets

P Blinov, M Avetisian - Proceedings of the Fifth Social Media …, 2020 - aclanthology.org
In this paper we present the drug adverse effects detection system developed during our
participation in the Social Media Mining for Health Applications Shared Task 2020. We …

BERT based adverse drug effect tweet classification

T Kayastha, P Gupta… - Proceedings of the Sixth …, 2021 - aclanthology.org
This paper describes models developed for the Social Media Mining for Health (SMM4H)
2021 shared tasks. Our team participated in the first subtask that classifies tweets with …

BERT implementation for detecting adverse drug effects mentions in Russian

A Gusev, A Kuznetsova, A Polyanskaya… - Proceedings of the fifth …, 2020 - aclanthology.org
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 …

Towards text processing pipelines to identify adverse drug events-related tweets: university of michigan@ SMM4H 2019 task 1

VGV Vydiswaran, G Ganzel, B Romas… - Proceedings of the …, 2019 - aclanthology.org
We participated in Task 1 of the Social Media Mining for Health Applications (SMM4H) 2019
Shared Tasks on detecting mentions of adverse drug events (ADEs) in tweets. Our approach …

Want to identify, extract and normalize adverse drug reactions in tweets? use roberta

KS Kalyan, S Sangeetha - arXiv preprint arXiv:2006.16146, 2020 - arxiv.org
This paper presents our approach for task 2 and task 3 of Social Media Mining for Health
(SMM4H) 2020 shared tasks. In task 2, we have to differentiate adverse drug reaction (ADR) …