Counterfactual Inference-based Data Augmentation for Drug-side effect Associations Prediction

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成果类型：

会议论文

作者：

Wenjie Yao;Weizhong Zhao;Xiaowei Xu;Xingpeng Jiang;Xianjun Shen;...

作者机构：

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

School of Computer, Central China Normal University, Wuhan, China

National Language Resources Monitoring and Research Center for Network Media, Central China Normal University, Wuhan, China

[Xiaowei Xu] Department of Information Science, University of Arkansas at Little Rock, Little Rock, AR, USA

[Wenjie Yao] Hubei Provincial Key Laboratory of Artificial Intelligence and Smart Learning, Central China Normal University, Wuhan, China<&wdkj&>School of Computer, Central China Normal University, Wuhan, China

语种：

英文

关键词：

counterfactual inference;data augmentation;drug-side effect associations prediction;heterogeneous information network

年：

2023

页码：

1643-1648

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/BIBM58861.2023.10385879

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：

Detecting drug side effects is crucial in development of drugs. As publicly available biomedical data expands, researchers have devised numerous computational methods for predicting drug-side effect associations (DSAs). Among these, network-based approaches have gained significant attention in the biomedical field. However, the challenge of data scarcity poses a significant hurdle for existing DSAs prediction models. While various data augmentation methods have been created to solve the proble, most rely on random alterations to the original ne...

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Counterfactual Inference-based Data Augmentation for Drug-side effect Associations Prediction

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