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Deep learning for named entity recognition on Chinese electronic medical records: Combining deep transfer learning with multitask bi-directional LSTM RNN

Specific entity terms such as disease, test, symptom, and genes in Electronic Medical Record (EMR) can be extracted by Named Entity Recognition (NER). However, limited resources of labeled EMR pose a great challenge for mining medical entity terms. In this study, a novel multitask bi-directional RNN...

詳細記述

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書誌詳細
出版年:PLoS One
主要な著者: Dong, Xishuang, Chowdhury, Shanta, Qian, Lijun, Li, Xiangfang, Guan, Yi, Yang, Jinfeng, Yu, Qiubin
フォーマット: Artigo
言語:Inglês
出版事項: Public Library of Science 2019
主題:
オンライン・アクセス:https://ncbi.nlm.nih.gov/pmc/articles/PMC6497281/
https://ncbi.nlm.nih.gov/pubmed/31048840
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1371/journal.pone.0216046
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