title: Recognizing scientific artifacts in biomedical literature.
abstract: Today's search engines and digital libraries offer little or no support for discovering those scientific artifacts (hypotheses, supporting/contradicting statements, or findings) that form the core of scientific written communication. Consequently, we currently have no means of identifying central themes within a domain or to detect gaps between accepted knowledge and newly emerging knowledge as a means for tracking the evolution of hypotheses from incipient phases to maturity or decline. We present a hybrid Machine Learning approach using an ensemble of four classifiers, for recognizing scientific artifacts (ie, hypotheses, background, motivation, objectives, and findings) within biomedical research publications, as a precursory step to the general goal of automatically creating argumentative discourse networks that span across multiple publications. The performance achieved by the classifiers ranges from 15.30% to 78.39%, subject to the target class. The set of features used for classification has led to promising results. Furthermore, their use strictly in a local, publication scope, ie, without aggregating corpus-wide statistics, increases the versatility of the ensemble of classifiers and enables its direct applicability without the necessity of re-training.
authors: School of ITEE, University of Queensland, Australia.
authors: Tudor
authors: T
authors: Groza
authors: Hamed
authors: H
authors: Hassanzadeh
authors: Jane
authors: J
authors: Hunter
keywords: conceptualization zones; information extraction; scientific artifacts
references: BMC Bioinformatics. 2005;6 Suppl 1:S14
references: 15960826
references: BMC Bioinformatics. 2006 Jul 25;7:356
references: 16867190
references: Bioinformatics. 2012 Apr 1;28(7):991-1000
references: 22321698
references: BMC Bioinformatics. 2008 Nov 19;9 Suppl 11:S10
references: 19025686
references: J Biomed Inform. 2009 Oct;42(5):905-11
references: 19535010
references: Biomed Inform Insights. 2012;5(Suppl. 1):77-85
references: 22879763
references: Comput Biol Chem. 2008 Aug;32(4):287-91
references: 18467180
references: Bioinformatics. 2008 Sep 15;24(18):2086-93
references: 18718948
references: Int J Med Inform. 2006 Jun;75(6):468-87
references: 16112609
references: Environ Health. 2003 Dec 16;2(1):16
references: 14678569
references: Biomed Inform Insights. 2012;5(Suppl. 1):185-93
references: 22879775
references: J Biomed Inform. 2008 Aug;41(4):580-7
references: 18272430
references: J Biomed Inform. 2012 Feb;45(1):156-64
references: 22056694
references: J Biomed Inform. 2008 Oct;41(5):739-51
references: 18583197
references: BMC Bioinformatics. 2011 Oct 10;12:393
references: 21985429
references: J Am Med Inform Assoc. 2009 Mar-Apr;16(2):247-55
references: 19074302