Recognizing scientific artifacts in biomedical literature

Groza, Tudor, Hassanzadeh, Hamed and Hunter, Jane (2013) Recognizing scientific artifacts in biomedical literature. Biomedical Informatics Insights, 6 15-27. doi:10.4137/BII.S11572

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Author Groza, Tudor
Hassanzadeh, Hamed
Hunter, Jane
Title Recognizing scientific artifacts in biomedical literature
Journal name Biomedical Informatics Insights   Check publisher's open access policy
ISSN 1178-2226
Publication date 2013-04-02
Year available 2013
Sub-type Article (original research)
DOI 10.4137/BII.S11572
Open Access Status DOI
Volume 6
Start page 15
End page 27
Total pages 13
Place of publication Auckland, New Zealand
Publisher Libertas Academica
Collection year 2014
Language eng
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.
Keyword Scientific artifacts
Conceptualization zones
Information extraction
Q-Index Code C1
Q-Index Status Confirmed Code
Institutional Status UQ

Document type: Journal Article
Sub-type: Article (original research)
Collections: Official 2014 Collection
School of Information Technology and Electrical Engineering Publications
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Created: Mon, 16 Dec 2013, 21:02:11 EST by Dr Tudor Groza on behalf of School of Information Technol and Elec Engineering