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Argumentation about Treatment Efficacy

  • Nikos Gorogiannis
  • Anthony Hunter
  • Vivek Patkar
  • Matthew Williams
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5943)

Abstract

The volume and complexity of knowledge produced by medical research calls for the development of technology for automated management and analysis of such knowledge. In this paper, we identify scenarios where a researcher or a clinician may wish to use automated systems for analysing knowledge from clinical trials. For this, we propose a language for encoding, capturing and synthesising knowledge from clinical trials and a framework that allows the construction of arguments from such knowledge. We develop this framework and demonstrate its use on a case study regarding chemotherapy regimens for ovarian cancer.

Keywords

Ovarian Cancer Trial Result Inference Rule Outcome Indicator Clinical Trial Result 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Nikos Gorogiannis
    • 1
  • Anthony Hunter
    • 1
  • Vivek Patkar
    • 2
  • Matthew Williams
    • 3
  1. 1.Department of Computer ScienceUniversity College LondonLondonUK
  2. 2.University College London Cancer InstituteLondonUK
  3. 3.Mount Vernon Hospital, NorthwoodMiddlesexUK

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