| 中文电子病历命名实体识别方法研究 |
| 投稿时间：2019-09-24 点此下载全文 |
| 引用本文：马欢欢,孔繁之,高建强.中文电子病历命名实体识别方法研究[J].医学信息学杂志,2020,41(4):24-29 |
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| 基金项目:教育部产学合作协同育人项目“高精度人脸识别技术与教学平台建设研究”（项目编号：201801245011）。 |
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| 中文摘要:针对中文电子病历命名实体识别任务中存在的边界划分不准确、实体识别率不高等问题,提出基于深度学习的CNN-BiLSTM-CRF模型,详细阐述模型结构与原理,采集3 127份中文电子病历数据进行实验以验证模型性能,结果表明该模型具有较好的识别效果及性能。 |
| 中文关键词:中文电子病历 命名实体识别 卷积神经网络 |
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| Study on Named Entity Recognition Method of Chinese Electronic Medical Records |
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| Abstract:Aiming at the problems of inaccurate boundary division and low entity recognition rate in the Named Entity Recognition (NER) task of Chinese Electronic Medical Records (EMR), the paper proposes a CNN-BiLSTM-CRF model based on deep learning, expounds the structure and principle of the model in detail, and collects 3 127 Chinese EMR for experiments to verify the performance of the model. The results show that this model achieves better recognition effect and better performance. |
| keywords:Chinese Electronic Medical Records(EMR) Named Entity Recognition(NER) Convolutional Neural Network(CNN) |
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