NLPExplorer

SMM4H - 2020

Total Papers:- 33

Total Papers accross all years:- 163

Total Citations :- 0

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Automatic Detecting for Health-related Twitter Data with BioBERT

Yang Bai | Xiaobing Zhou |

Annotating Patient Information Needs in Online Diabetes Forums

CLaC at SMM4H 2020: Birth Defect Mention Detection

Parsa Bagherzadeh | Sabine Bergler |

Automatic Classification of Tweets Mentioning a Medication Using Pre-trained Sentence Encoders

Laiba Mehnaz |

BERT Implementation for Detecting Adverse Drug Effects Mentions in Russian

Andrey Gusev | Anna Kuznetsova | Anna Polyanskaya | Egor Yatsishin |

HITSZ-ICRC: A Report for SMM4H Shared Task 2020-Automatic Classification of Medications and Adverse Effect in Tweets

Xiaoyu Zhao | Ying Xiong | Buzhou Tang |

Overview of the Fifth Social Media Mining for Health Applications (#SMM4H) Shared Tasks at COLING 2020

NLP@VCU: Identifying Adverse Effects in English Tweets for Unbalanced Data

Darshini Mahendran | Cora Lewis | Bridget McInnes |

Sentence Transformers and Bayesian Optimization for Adverse Drug Effect Detection from Twitter

Oguzhan Gencoglu |

Towards Preemptive Detection of Depression and Anxiety in Twitter

David Owen | Jose Camacho-Collados | Luis Espinosa Anke |

Sentence Contextual Encoder with BERT and BiLSTM for Automatic Classification with Imbalanced Medication Tweets

Olanrewaju Tahir Aduragba | Jialin Yu | Gautham Senthilnathan | Alexandra Crsitea |

How Far Can We Go with Just Out-of-the-box BERT Models?

Lucie Gattepaille |

Sentence Classification with Imbalanced Data for Health Applications

Farhana Ferdousi Liza |

SMM4H Shared Task 2020 - A Hybrid Pipeline for Identifying Prescription Drug Abuse from Twitter: Machine Learning, Deep Learning, and Post-Processing