DS4DH at #SMM4H 2023: Zero-Shot Adverse Drug Events Normalization using Sentence Transformers and Reciprocal-Rank Fusion

08/15/2023

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This paper outlines the performance evaluation of a system for adverse drug event normalization, developed by the Data Science for Digital Health group for the Social Media Mining for Health Applications 2023 shared task 5. Shared task 5 targeted the normalization of adverse drug event mentions in Twitter to standard concepts from the Medical Dictionary for Regulatory Activities terminology. Our system hinges on a two-stage approach: BERT fine-tuning for entity recognition, followed by zero-shot normalization using sentence transformers and reciprocal-rank fusion. The approach yielded a precision of 44.9 performance in shared task 5 by 10 among all participants. These results substantiate the effectiveness of our approach and its potential application for adverse drug event normalization in the realm of social media text mining.

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DS4DH at #SMM4H 2023: Zero-Shot Adverse Drug Events Normalization using Sentence Transformers and Reciprocal-Rank Fusion

Boosting Adverse Drug Event Normalization on Social Media: General-Purpose Model Initialization and Biomedical Semantic Text Similarity Benefit Zero-Shot Linking in Informal Co

Detecting Adverse Drug Reactions from Twitter through Domain-Specific Preprocessing and BERT Ensembling

Enhancing Pharmacovigilance with Drug Reviews and Social Media

Improving Adverse Drug Event Extraction with SpanBERT on Different Text Typologies

Concept Extraction to Identify Adverse Drug Reactions in Medical Forums: A Comparison of Algorithms

Adapting Phrase-based Machine Translation to Normalise Medical Terms in Social Media Messages

Drug and Disease Interpretation Learning with Biomedical Entity Representation Transformer

DS4DH at #SMM4H 2023: Zero-Shot Adverse Drug Events Normalization using Sentence Transformers and Reciprocal-Rank Fusion

Related Research

Boosting Adverse Drug Event Normalization on Social Media: General-Purpose Model Initialization and Biomedical Semantic Text Similarity Benefit Zero-Shot Linking in Informal Co

Detecting Adverse Drug Reactions from Twitter through Domain-Specific Preprocessing and BERT Ensembling

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