Top-Level MeSH Disease Terms Are Not Linearly Separable in Clinical Trial Abstracts

  • Joël Kuiper
  • Gert van Valkenhoef
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7885)

Abstract

Assessments of the efficacy and safety of medical interventions are based on systematic reviews of clinical trials. Systematic reviewing requires the screening of vast amounts of publications, which is currently done by hand. To reduce the number of publications that are screened manually, we propose the automated classification of publications by disease category using Support Vector Machines. We base our classification on the ontological structure of the (MeSH) by treating all terms as their top-level disease category. Unfortunately the resulting classifier lacks sufficient sensitivity for use by systematic reviewers. We argue that this is partially due to the inseparability of the terminology into the disease categories and discuss how future work could address this problem.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Joël Kuiper
    • 1
  • Gert van Valkenhoef
    • 1
    • 2
  1. 1.Faculty of Economics and BusinessUniversity of GroningenGroningenThe Netherlands
  2. 2.Department of Epidemiology, University Medical Center GroningenUniversity of GroningenGroningenThe Netherlands

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