Biomedical document triage using a hierarchical attention-based capsule network
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RESEARCH
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Biomedical document triage using a hierarchical attention-based capsule network Jian Wang, Mengying Li, Qishuai Diao, Hongfei Lin, Zhihao Yang and YiJia Zhang* From The 18th Asia Pacific Bioinformatics Conference Seoul, Korea. 18-20 August 2020 *Correspondence: [email protected] Dalian University of Technology, The School of Computer Science and Technology, 116024 Dalian, China
Abstract Background: Biomedical document triage is the foundation of biomedical information extraction, which is important to precision medicine. Recently, some neural networks-based methods have been proposed to classify biomedical documents automatically. In the biomedical domain, documents are often very long and often contain very complicated sentences. However, the current methods still find it difficult to capture important features across sentences. Results: In this paper, we propose a hierarchical attention-based capsule model for biomedical document triage. The proposed model effectively employs hierarchical attention mechanism and capsule networks to capture valuable features across sentences and construct a final latent feature representation for a document. We evaluated our model on three public corpora. Conclusions: Experimental results showed that both hierarchical attention mechanism and capsule networks are helpful in biomedical document triage task. Our method proved itself highly competitive or superior compared with other state-of-the-art methods. Keywords: Biomedical document triage, Capsule network, Hierarchical attention mechanism, Biomedical literature
Background Biomedical natural language processing (BioNLP) has an important role in the framework for implementing precision medicine [1–3] . Biomedical document triage is an important task in BioNLP, and is the first step in the literature curation workflow [4, 5]. Biomedical document triage helps curators and researchers focus on the biomedical literature that contains information relevant to their tasks [6, 7]. In the past decade, biomedical document triage has been an important shared task in the BioCreative challenge community. For example, BioCreative II (IAS) [8] and III
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