Literature Classification of Individual Reports of Adverse Drug Reactions Based on BERT and CNN
Clinically,the death caused by adverse drug reactions and the sharp increase in hospitalization and outpatient expenses caused by improper drug use have become one of the main problems faced by clinical safe and rational drug use.At present,the research of adverse drug reactions retrospective analysis and literature analysis is mostly based on published literature informa-tion.Academic literature is one of the important sources of data,and how to automatically process data in batches is particularly important.According to the unique expression of traditional Chinese medicine text,based on BERT and its combination algo-rithm,through the comparison experiment of text classification technology,an efficient and fast classification method for the liter-ature data of adverse drug reactions case reports is established,and then the types of adverse drug reactions are distinguished.Ex-perimental results show that the classification accuracy of BERT algorithm reaches 99.75％,which can accurately and efficiently classify the reported literature of adverse drug reactions,and has important value and significance for auxiliary medical treatment and constructing structured data of medical texts.
Adverse drug reactionsIndividual case literature reportMedical text classificationDeep learningBERT
NETL
NSTL
万方数据
