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A robust approach to extract biomedical events from literature
Author(s) -
Quoc-Chinh Bui,
P.M.A. Sloot
Publication year - 2012
Publication title -
bioinformatics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.599
H-Index - 390
eISSN - 1367-4811
pISSN - 1367-4803
DOI - 10.1093/bioinformatics/bts487
Subject(s) - computer science , task (project management) , binary relation , process (computing) , binary number , code (set theory) , event (particle physics) , source code , biomedical text mining , artificial intelligence , data mining , template , information retrieval , text mining , programming language , set (abstract data type) , mathematics , physics , discrete mathematics , quantum mechanics , economics , management , arithmetic
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.

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