title: Creation of a corpus for evidence based medicine summarisation.
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.
  
  
  OBJECTIVE
  To produce a corpus for research in EBM summarisation.
  
  
  METHODS
  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.
  
  
  CONCLUSIONS
  The corpus is now available for the research community at http://sourceforge.net/projects/ebmsumcorpus.
authors.affiliation: Department of Computing, Macquarie University, Australia.
authors.forename: Diego
authors.initials: D
authors.lastname: Mollá
authors.forename: María Elena
authors.initials: ME
authors.lastname: Santiago-Martínez
keywords: Evidence Based Medicine; corpora; natural language processing.; text summarisation