Named Entity Recognition of Chinese Electronic Medical Record Based on BERT and Domain Dictionary
The beginning of medical data mining is CNER(named entity recognition of Chinese electronic medical record).The target of medical data mining is to recognize unstructured text from related entities(anatomical parts,drugs,image examina-tion,etc.).Based on the need of improving the accuracy of CNER,This paper designs the BERT-BiLSTM-CRF model fusion do-main dictionary technology,which can fully combine the context semantic relationship,solve the polysemy problem,and obtain the long-distance dependence of EMR sentences.When CNER uses the BERT-BiLSTM-CRF model to fuse the domain dictionary tech-nology,the value of F1 has been confirmed by the experimental results,which is of great significance to the construction knowledge graph,clinical decision support system and medical record quality control system.
Chinese electronic medical recordnamed entity recognitionBERT-BiLSTM-CRFdomain dictionary
国家科技期刊平台
NSTL
万方数据
