A corpus for research in text processing for evidence based medicine
Evidence based medicine (EBM) urges the medical doctor to incorporate the latest available clinical evidence at point of care. A major stumbling block in the practice of EBM is the difficulty to keep up to date with the clinical advances. In this paper we describe a corpus designed for the development and testing of text processing tools for EBM, in particular for tasks related to the extraction and summarisation of answers and corresponding evidence related to a clinical query. The corpus is based on material from the Clinical Inquiries section of The Journal of Family Practice. It was gathered and annotated by a combination of automated information extraction, crowdsourcing tasks, and manual annotation. It has been used for the original summarisation task for which it was designed, as well as for other related tasks such as the appraisal of clinical evidence and the clustering of the results. The corpus is available at SourceForge (http://sourceforge.net/projects/ebmsumcorpus/).
KeywordsCorpus Evidence based medicine Annotation Crowdsourcing Text summarization
Parts of this research were funded by the Oak Ridge Institute for Science and Education (ORISE), Macquarie University, and the Commonwealth Scientific and Industrial Research Organisation (CSIRO).
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