Biomedical event extraction with a novel combination strategy based on hybrid deep neural networks

BMC Bioinformatics

Lvxing Zhu¹  Haoran Zheng² 

[1] School of Computer Science and Technology, University of Science and Technology of China, Huangshan Road, 230026, Hefei, People’s Republic of China;School of Computer Science and Technology, University of Science and Technology of China, Huangshan Road, 230026, Hefei, People’s Republic of China;Anhui Key Laboratory of Software Engineering in Computing and Communication, University of Science and Technology of China, Huangshan Road, 230026, Hefei, People’s Republic of China;Anhui Province Key Lab. of Big Data Analysis and Application, University of Science and Technology of China, Huangshan Road, 230026, Hefei, People’s Republic of China;

关键词: Event extraction;    Biomedical text;    Deep learning Neural network;   

DOI  :  10.1186/s12859-020-3376-2

来源: Springer

【 摘 要 】

BackgroundBiomedical event extraction is a fundamental and in-demand technology that has attracted substantial interest from many researchers. Previous works have heavily relied on manual designed features and external NLP packages in which the feature engineering is large and complex. Additionally, most of the existing works use the pipeline process that breaks down a task into simple sub-tasks but ignores the interaction between them. To overcome these limitations, we propose a novel event combination strategy based on hybrid deep neural networks to settle the task in a joint end-to-end manner.ResultsWe adapted our method to several annotated corpora of biomedical event extraction tasks. Our method achieved state-of-the-art performance with noticeable overall F1 score improvement compared to that of existing methods for all of these corpora.ConclusionsThe experimental results demonstrated that our method is effective for biomedical event extraction. The combination strategy can reconstruct complex events from the output of deep neural networks, while the deep neural networks effectively capture the feature representation from the raw text. The biomedical event extraction implementation is available online at http://www.predictor.xin/event_extraction.

【 授权许可】

CC BY