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Australas Med J. 2012;5(9):503-6. doi: 10.4066/AMJ.2012.1375. Epub 2012 Sep 30.

Creation of a corpus for evidence based medicine summarisation.

Author information

  • 1Department of Computing, Macquarie University, Australia.

Abstract

BACKGROUND:

Automated text summarisers that find the best clinical evidence reported in collections of medical literature are of potential benefit for the practice of Evidence Based Medicine (EBM). Research and development of text summarisers for EBM, however, is impeded by the lack of corpora to train and test such systems.

AIMS:

To produce a corpus for research in EBM summarisation.

METHOD:

We sourced the "Clinical Inquiries" section of the Journal of Family Practice (JFP) and obtained a sizeable sample of questions and evidence based summaries. We further processed the summaries by combining automated techniques, human annotations, and crowdsourcing techniques to identify the PubMed IDs of the references.

RESULTS:

The corpus has 456 questions, 1,396 answer components, 3,036 answer justifications, and 2,908 references.

CONCLUSION:

The corpus is now available for the research community at http://sourceforge.net/projects/ebmsumcorpus.

KEYWORDS:

Evidence Based Medicine; corpora; natural language processing.; text summarisation

PMID:
23115585
[PubMed]
PMCID:
PMC3477779
Free PMC Article
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