GONG Lejun1,2*, LIU Xiaolin1,2, GAO Zhihong3, LI Huakang1,4,5
（1 School of Computer Science, Nanjing University of Posts and Telecommunications, Nanjing 210023, Jiangsu, China;2 Jiangsu Key Lab of Big Data Security & Intelligent Processing, Nanjing 210023, Jiangsu, China;3 Zhejiang Engineering Research Center of Intelligent Medicine, Wenzhou 325035, Zhejiang, China;4 Key Laboratory of Urban Land Resources Monitoring and Simulation, Ministry of Natural Resources, Shenzhen 518034, Guangdong, China;5 Suzhou Privacy Information Technology Company, Suzhou 215011, Jiangsu, China）
Abstract:
Drug-drug interaction (DDI) is the difference between pharmacodynamics and pharmacokinetics of different drugs, which may produce unpredictable side effects or even threaten the life safety of patients. With the rapid development of information technology and the increase of exponential biomedical literature, it is possible to extract drug interactions from texts.A two-layer drug relationship extraction model based on the fusion of bidirectional GRU (bi-gated recurrent unit, BiGRU) and convolutional neural network (CNN) is proposed.DDIExtraction 2013 is used as data set to evaluate multiple groups of experiments, and obtain the highest comprehensive evaluation rate of 75% is obtained. Compared with other′s works, the two-layer model based on bidirectional GRU and CNN can effectively extract the drug interaction relationship in the text.
KeyWords:
drug-drug interaction(DDI); biomedical relationship extraction; drug relationship extraction; GRU; CNN
