BERT based Transformers lead the way in Extraction of Health Information from Social Media (original) (raw)

KFU NLP Team at SMM4H 2019 Tasks: Want to Extract Adverse Drugs Reactions from Tweets? BERT to The Rescue

Elena Tutubalina

Proceedings of the Fourth Social Media Mining for Health Applications (#SMM4H) Workshop & Shared Task

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Fine-tuning BERT to classify COVID19 tweets containing symptoms

Rajarshi Roychoudhury

Proceedings of the Sixth Social Media Mining for Health (#SMM4H) Workshop and Shared Task

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UACH-INAOE at SMM4H: a BERT based approach for classification of COVID-19 Twitter posts

Jesus Daniel Baez Lopez

Proceedings of the Sixth Social Media Mining for Health (#SMM4H) Workshop and Shared Task, 2021

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ULD-NUIG at Social Media Mining for Health Applications (#SMM4H) Shared Task 2021

Priya Rani

Proceedings of the Sixth Social Media Mining for Health (#SMM4H) Workshop and Shared Task, 2021

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

Sougata Saha

2020

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UIT-HSE at WNUT-2020 Task 2: Exploiting CT-BERT for Identifying COVID-19 Information on the Twitter Social Network

Thùy Nguyễn

Proceedings of the Sixth Workshop on Noisy User-generated Text (W-NUT 2020), 2020

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IRLab@IITBHU at WNUT-2020 Task 2: Identification of informative COVID-19 English Tweets using BERT

Supriya Chanda

Proceedings of the Sixth Workshop on Noisy User-generated Text (W-NUT 2020), 2020

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Data and systems for medication-related text classification and concept normalization from Twitter: insights from the Social Media Mining for Health (SMM4H)-2017 shared task

Goran Nenadic

Journal of the American Medical Informatics Association : JAMIA, 2018

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MIDAS@SMM4H-2019: Identifying Adverse Drug Reactions and Personal Health Experience Mentions from Twitter

Yaman Kumar

Proceedings of the Fourth Social Media Mining for Health Applications (#SMM4H) Workshop & Shared Task

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Overview of the Sixth Social Media Mining for Health Applications (#SMM4H) Shared Tasks at NAACL 2021

Martin Krallinger

Proceedings of the Sixth Social Media Mining for Health (#SMM4H) Workshop and Shared Task, 2021

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Identifying COVID-19 cases and extracting patient reported symptoms from Reddit using natural language processing

Efe Eworuke

Scientific Reports

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Team UKNLP: Detecting ADRs, Classifying Medication Intake Messages, and Normalizing ADR Mentions on Twitter

Sifei Han

2017

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Automatic Extraction of Medication Names in Tweets as Named Entity Recognition

Virginia Adams

arXiv (Cornell University), 2021

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SemEval-2017 Task 4: Sentiment Analysis in Twitter using BERT

Rupak Kumar Das

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Improving Adverse Drug Event Extraction with SpanBERT on Different Text Typologies

Emmanuele Chersoni

ArXiv, 2021

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ISWARA at WNUT-2020 Task 2: Identification of Informative COVID-19 English Tweets using BERT and FastText Embeddings

Isnaini Nurul Khasanah

Proceedings of the Sixth Workshop on Noisy User-generated Text (W-NUT 2020), 2020

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IIITN NLP at SMM4H 2021 Tasks: Transformer Models for Classification on Health-Related Imbalanced Twitter Datasets

prajwal nakhate

Proceedings of the Sixth Social Media Mining for Health (#SMM4H) Workshop and Shared Task, 2021

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Identification of Disease or Symptom terms in Reddit to Improve Health Mention Classification

Usman Naseem

Proceedings of the ACM Web Conference 2022

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A Novel Approach to Train Diverse Types of Language Models for Health Mention Classification of Tweets

sheraz ahmed

arXiv (Cornell University), 2022

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Principle Base Approach for Classifying Tweets with Flu-related Information in NTCIR-13 MedWeb Task

Hong-jie Dai

2017

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Benchmarking for Public Health Surveillance tasks on Social Media with a Domain-Specific Pretrained Language Model

Usman Naseem

Proceedings of NLP Power! The First Workshop on Efficient Benchmarking in NLP

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Boosting Transformers using Background Knowledge, or how to detect Drug Mentions in Social Media using Limited Data

Lisa Raithel

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CXP949 at WNUT-2020 Task 2: Extracting Informative COVID-19 Tweets -- RoBERTa Ensembles and The Continued Relevance of Handcrafted Features

Harish Tayyar Madabushi

arXiv (Cornell University), 2020

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COVID-19 Tweets Analysis through Transformer Language Models

Abdul Hameed Azeemi

2021

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SunBear at WNUT-2020 Task 2: Improving BERT-Based Noisy Text Classification with Knowledge of the Data domain

Linh Nguyễn Trần Bảo

Proceedings of the Sixth Workshop on Noisy User-generated Text (W-NUT 2020), 2020

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