Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/96085
Title: A robust approach to extract biomedical events from literature
Authors: Bui, Quoc-Chinh
Sloot, Peter M. A.
Issue Date: 2012
Source: Bui, Q. C. & Sloot, P. M. A. (2012). A robust approach to extract biomedical events from literature. Bioinformatics, 28(20), 2654-2661.
Series/Report no.: Bioinformatics
Abstract: Motivation: The abundance of biomedical literature has attracted significant interest in novel methods to automatically extract biomedical relations from the literature. Until recently, most research was focused on extracting binary relations such as protein–protein interactions and drug–disease relations. However, these binary relations cannot fully represent the original biomedical data. Therefore, there is a need for methods that can extract fine-grained and complex relations known as biomedical events. Results: In this article we propose a novel method to extract biomedical events from text. Our method consists of two phases. In the first phase, training data are mapped into structured representations. Based on that, templates are used to extract rules automatically. In the second phase, extraction methods are developed to process the obtained rules. When evaluated against the Genia event extraction abstract and full-text test datasets (Task 1), we obtain results with F-scores of 52.34 and 53.34, respectively, which are comparable to the state-of-the-art systems. Furthermore, our system achieves superior performance in terms of computational efficiency.
URI: https://hdl.handle.net/10356/96085
http://hdl.handle.net/10220/10109
DOI: http://dx.doi.org/10.1093/bioinformatics/bts487
Rights: © 2012 The Author(s). Published by Oxford University Press. This paper was published in Bioinformatics and is made available as an electronic reprint (preprint) with permission of The Author(s). The paper can be found at the following official DOI: [http://dx.doi.org/10.1093/bioinformatics/bts487].  One print or electronic copy may be made for personal use only. Systematic or multiple reproduction, distribution to multiple locations via electronic or other means, duplication of any material in this paper for a fee or for commercial purposes, or modification of the content of the paper is prohibited and is subject to penalties under law.
Fulltext Permission: open
Fulltext Availability: With Fulltext
Appears in Collections:SCSE Journal Articles

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