An Effective Microbial–drug Relation Extraction Model Based on Dual Graph Convolutional Networks

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成果类型：

会议论文

作者：

Ruizhe Zhang;Dandan Li;Ying Xiao;Weizhong Zhao;Xingpeng Jiang;...

作者机构：

Hubei Provincial Key Laboratory of Artificial Intelligence and Smart Learning, Central China Normal University, WuHan, Hubei, PR China

School of Computer, Central China Normal University, WuHan, Hubei, PR China

National Language Resources Monitoring & Research Center for Network Media, Central China Normal University, WuHan, Hubei, PR China

[Ruizhe Zhang; Dandan Li; Ying Xiao; Weizhong Zhao; Xingpeng Jiang; Xianjun Shen] Hubei Provincial Key Laboratory of Artificial Intelligence and Smart Learning, Central China Normal University, WuHan, Hubei, PR China<&wdkj&>School of Computer, Central China Normal University, WuHan, Hubei, PR China<&wdkj&>National Language Resources Monitoring & Research Center for Network Media, Central China Normal University, WuHan, Hubei, PR China

语种：

英文

关键词：

microbial-drug relation extraction;graph convolutional network;semantic feature;syntactic feature

年：

2023

页码：

984-987

会议名称：

2023 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)

会议论文集名称：

2023 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)

会议时间：

05 December 2023

会议地点：

Istanbul, Turkiye

出版者：

IEEE

ISBN：

979-8-3503-3749-5

DOI：

10.1109/BIBM58861.2023.10385893

基金类别：

10.13039/501100001809-National Natural Science Foundation of China 10.13039/501100003819-Natural Science Foundation of Hubei Province

机构署名：

本校为第一机构

院系归属：

计算机学院

摘要：

Microbe-drug interactions, which refer to the effects of drugs on microorganisms, play a crucial role in the realm of studying antibiotic-resistant bacteria and the development of antimicrobial agents. With the rapid progress in biomedical field, numerous experimental results containing validated microbe-drug interactions have been available in scientific articles. However, since failing to employ domain knowledge, traditional natural language processing methods encounter challenges in accurately identifying microbe and drug entities. Moreover, the unstructured characteristics and semantic com...

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An Effective Microbial–drug Relation Extraction Model Based on Dual Graph Convolutional Networks

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