Drug Drug Interaction Extraction from Literature Using a Skeleton Long Short Term Memory Neural Network
文献类型：会议论文
| 作者 | Liang Gu; Zhenchao Jiang; Qingshan Jiang |
| 出版日期 | 2017 |
| 会议日期 | 2017 |
| 会议地点 | 美国 |
| 英文摘要 | Drug Drug Interactions (DDIs) can cause harmful effect. Two shared tasks, DDIExtraction 2011 and DDIExtraction 2013, have been held to promote the implementation and comparative assessment of natural language processing techniques in the field of the pharmacovigilance domain. However, few model can meanwhile achieve state-of-the-art performance on both tasks. A major reason is the lack of representation of DDI instance structure in common. Therefore,in this paper, we propose a novel method to make full use of the DDI structure based on deep learning, in which we grasp the skeleton structure of DDI instances by a skeleton long short term memory (skeleton-LSTM) network. The experimental results show that our method can achieve an F-score of 0.677 on DDIExtraction 2011 and an F-score of 0.714 on DDIExtraction 2013, both of which are state-of-the-art。 |
| 语种 | 英语 |
| 源URL | [http://ir.siat.ac.cn:8080/handle/172644/12689]  |
| 专题 | 深圳先进技术研究院_数字所 |
| 作者单位 | 2017 |
| 推荐引用方式 GB/T 7714 | Liang Gu,Zhenchao Jiang,Qingshan Jiang. Drug Drug Interaction Extraction from Literature Using a Skeleton Long Short Term Memory Neural Network[C]. 见:. 美国. 2017. |
入库方式： OAI收割
来源：深圳先进技术研究院
浏览0
下载0
收藏0
其他版本
除非特别说明，本系统中所有内容都受版权保护，并保留所有权利。