Adverse Drug Event Extraction

Adverse drug event (ADE) extraction uses natural language processing (NLP) to automatically identify mentions of adverse reactions to medications within various text sources, such as medical literature, social media, and electronic health records. Current research focuses on improving the accuracy and robustness of these extraction methods, particularly using deep learning models like transformers (e.g., BERT) and large language models (LLMs), often employing ensemble techniques to combine their strengths. This work is crucial for enhancing pharmacovigilance efforts, enabling faster detection of safety signals and improving public health surveillance by efficiently analyzing massive volumes of textual data.