Sentence Transformers and Bayesian Optimization for Adverse Drug Effect Detection from Twitter
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 approach utilizes multilingual sentence embeddings (sentence-BERT) for representing tweets and Bayesian hyperparameter optimization of sample weighting parameter for counterbalancing high class imbalance.
Code (0)
등록된 구현이 없습니다.
Tasks
Bayesian OptimizationHyperparameter OptimizationSentenceSentence EmbeddingsTask 2Similar Papers 제목 키워드 기반
DS4DH at #SMM4H 2023: Zero-Shot Adverse Drug Events Normalization using Sentence Transformers and Reciprocal-Rank Fusion
This paper outlines the performance evaluation of a system for adverse drug event normalization, developed by the Data Science for Digital Health (DS4DH) group for the Social Media Mining for Health Applications (SMM4H) …
SentenceMeasuring Adverse Drug Effects on Multimorbity using Tractable Bayesian Networks
Managing patients with multimorbidity often results in polypharmacy: the prescription of multiple drugs. However, the long-term effects of specific combinations of drugs and diseases are typically unknown. In particular,…
A Dual-Attention Network for Joint Named Entity Recognition and Sentence Classification of Adverse Drug Events
An adverse drug event (ADE) is an injury resulting from medical intervention related to a drug. Automatic ADE detection from text is either fine-grained (ADE entity recognition) or coarse-grained (ADE assertive sentence …
Classificationnamed-entity-recognitionNamed Entity RecognitionNamed Entity Recognition (NER)+2Annotation of Adverse Drug Reactions in Patients' Weblogs
Adverse drug reactions are a severe problem that significantly degrade quality of life, or even threaten the life of patients. Patient-generated texts available on the web have been gaining attention as a promising sourc…
ArticlesGASCADE: Grouped Summarization of Adverse Drug Event for Enhanced Cancer Pharmacovigilance
In the realm of cancer treatment, summarizing adverse drug events (ADEs) reported by patients using prescribed drugs is crucial for enhancing pharmacovigilance practices and improving drug-related decision-making. While …
Abstractive Text SummarizationDecision MakingDecoderPharmacovigilance