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 developme...

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Publicado en:Language Resources & Evaluation Vol. 50; no. 4; pp. 705 - 728
Autores principales: Mollá, Diego, Santiago-Martínez, María, Sarker, Abeed, Paris, Cécile
Formato: Artículo
Publicado: Springer Nature Dec2016
Materias:
Acceso en línea:Ver este registro en EBSCOhost
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          Mollá, Diego
          Santiago-Martínez, María
          Sarker, Abeed
          Paris, Cécile
        affil:
          Department of Computing , Macquarie University , Sydney Australia
          CSIRO Marsfield , Cnr Vimiera and Pembroke Roads Sydney Australia
      su:
        Evidence-based medicine
        Decision making in clinical medicine
        Crowdsourcing
        Text processing (Computer science)
        Data extraction
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          Evidence-based medicine
          Decision making in clinical medicine
          Crowdsourcing
          Text processing (Computer science)
          Data extraction
      keyword:
        Annotation
        Corpus
        Evidence based medicine
        Text summarization
      ab: 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 ().
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    language: English
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      custom: Language Resources & Evaluation is a copyright of Springer, 2016. All Rights Reserved.
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