The electronic medical record data contains a large number of medical entities,and the automatic recogni-tion of these entities is beneficial for improving the understanding of electronic medical records.The electronic medi-cal record data contains professional medical terms and a large number of non-standard medical vocabulary.Rare words,long difficult words and omission in medical records bring challenges to medical entity recognition.To solve this problem,this paper proposes a medical entity recognition method based on graph attention network and syntax fusion.This method combines the co-occurrence relationship between words and the rules of syntactic dependency,and it realizes the fusion of various graph information by graph-attention network based on the construction of inter-active character-word relationship graph and dependency relationship graph of electronic medical record data.The experiment result reveals that the proposed method achieves 88.91％F1 value,which is 1.04％higher than the baseline model.
关键词
电子病历/命名实体识别/图注意力网络
Key words
electronic medical record/named entity recognition/graph attention network
维普
万方数据