A multitask bi-directional RNN model for named entity recognition on Chinese electronic medical records
Abstract Background Electronic Medical Record (EMR) comprises patients’ medical information gathered by medical stuff for providing better health care. Named Entity Recognition (NER) is a sub-field of information extraction aimed at identifying specific entity terms such as disease, test, symptom, g...
Main Authors: | Shanta Chowdhury, Xishuang Dong, Lijun Qian, Xiangfang Li, Yi Guan, Jinfeng Yang, Qiubin Yu |
---|---|
Format: | Article |
Language: | English |
Published: |
BMC
2018-12-01
|
Series: | BMC Bioinformatics |
Subjects: | |
Online Access: | http://link.springer.com/article/10.1186/s12859-018-2467-9 |
Similar Items
-
Named Entity Recognition for Chinese Electronic Medical Records Based on Multitask and Transfer Learning
by: Wenming Guo, et al.
Published: (2022-01-01) -
A Multitask Learning Approach for Named Entity Recognition by Exploiting Sentence-Level Semantics Globally
by: Wenzhi Huang, et al.
Published: (2022-09-01) -
EXTENDED DISTRIBUTED PROTOTYPICAL FOR BIOMEDICAL NAMED ENTITY RECOGNITION
by: Maan Tareq Abd, et al.
Published: (2017-12-01) -
Deep learning for named entity recognition on Chinese electronic medical records: Combining deep transfer learning with multitask bi-directional LSTM RNN.
by: Xishuang Dong, et al.
Published: (2019-01-01) -
Long short-term memory RNN for biomedical named entity recognition
by: Chen Lyu, et al.
Published: (2017-10-01)