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Database (Oxford). 2016 Mar 25;2016. pii: baw036. doi: 10.1093/database/baw036. Print 2016.

CD-REST: a system for extracting chemical-induced disease relation in literature.

Author information

1
School of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, TX 77030, USA.
2
School of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, TX 77030, USA hua.xu@uth.tmc.edu.

Abstract

Mining chemical-induced disease relations embedded in the vast biomedical literature could facilitate a wide range of computational biomedical applications, such as pharmacovigilance. The BioCreative V organized a Chemical Disease Relation (CDR) Track regarding chemical-induced disease relation extraction from biomedical literature in 2015. We participated in all subtasks of this challenge. In this article, we present our participation system Chemical Disease Relation Extraction SysTem (CD-REST), an end-to-end system for extracting chemical-induced disease relations in biomedical literature. CD-REST consists of two main components: (1) a chemical and disease named entity recognition and normalization module, which employs the Conditional Random Fields algorithm for entity recognition and a Vector Space Model-based approach for normalization; and (2) a relation extraction module that classifies both sentence-level and document-level candidate drug-disease pairs by support vector machines. Our system achieved the best performance on the chemical-induced disease relation extraction subtask in the BioCreative V CDR Track, demonstrating the effectiveness of our proposed machine learning-based approaches for automatic extraction of chemical-induced disease relations in biomedical literature. The CD-REST system provides web services using HTTP POST request. The web services can be accessed fromhttp://clinicalnlptool.com/cdr The online CD-REST demonstration system is available athttp://clinicalnlptool.com/cdr/cdr.html. Database URL:http://clinicalnlptool.com/cdr;http://clinicalnlptool.com/cdr/cdr.html.

PMID:
27016700
PMCID:
PMC4808251
DOI:
10.1093/database/baw036
[Indexed for MEDLINE]
Free PMC Article

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