A Pre-trained Language Model-based Method for Adverse Drug Events Extraction
Purpose/Significance To study the extraction method of adverse drug event(ADE)data from medical texts,and to pro-vide support for clinical drug risk management and scientific decision-making.Method/Process Based on pre-trained model,by com-bining the correlation between the two subtasks of entity recognition and relation extraction,a entity relation joint extraction method for ADE monitoring is designed.Result/Conclusion Experiments on the published ADE extraction dataset show that the proposed method is superior to existing methods and can effectively extract ADE information and its relation from medical texts,providing a powerful means for the discovery and monitoring of ADE.
adverse drug evententity relation extractionpre-trained modelnatural language processingmedicine
万方数据
维普
