医学信息2024，Vol.37Issue(1)：65-71,7.DOI:10.3969/j.issn.1006-1959.2024.01.012
基于K-BERT的中文妇产科电子病历实体识别研究
Research on Entity Recognition of Chinese Obstetrics and Gynecology Electronic Medical Records Based on K-BERT
张由 1李舫1
作者信息
- 1. 上海电力大学计算机科学与技术学院,上海 201306
- 折叠
摘要
Abstract
When the pre-trained model is used to name entity recognition of Chinese obstetrics and gynecology electronic medical records,BERT lacks certain professional knowledge in the medical field,which leads to the decline of its recognition performance.A pre-trained model based on knowledge graph-K-BERT name entity recognition model K-BERT-BiLSTM-CRF is proposed.The K-BERT pre-training model is used to obtain the semantic feature vector containing the medical background knowledge,and the bidirectional long short-term memory network(BiLSTM)and conditional random field(CRF)are used to extract the context-related features and solve the label offset problem to complete the entity recognition.Using the real obstetrics and gynecology medical electronic medical record data set for training,the F1 value of the K-BERT-BiLSTM-CRF model reached 90.04％.Experiments show that compared with the general BERT model,the K-BERT-BiLSTM-CRF name entity recognition model performs better in the field of Chinese obstetrics and gynecology electronic medical records,and the recognition effect is better.关键词
K-BERT/双向长短时记忆网络/条件随机场/妇产科电子病历/命名实体识别Key words
K-BERT/Bidirectional long short-term memory/Conditional random fields/Obstetrics and gynecology electronic medical records/Name entity recognition分类
信息技术与安全科学引用本文复制引用
张由,李舫..基于K-BERT的中文妇产科电子病历实体识别研究[J].医学信息,2024,37(1):65-71,7.
