Sparse estimation: applications in atrial fibrillation

Research output: ThesisDoctoral ThesisInternal

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Abstract

Finding important links between large numbers of factors is a topical issue. In this study, a mathematical method was developed allowing dominant links between a certain outcome and many possible predictive factors, or key interactions in a large complex network to be discovered by using relatively few data. This can be achieved by assuming that among the many possible links only a few are actually meaningful. This method has been successfully applied to, among other things, discovering key factors playing a role in the effectiveness of treatment strategies for atrial fibrillation, a type of cardiac arrhythmia.
Original languageEnglish
QualificationDoctor of Philosophy
Awarding Institution
  • Maastricht University
Supervisors/Advisors
  • Peeters, Ralf, Supervisor
  • Schotten, Ulrich, Supervisor
  • Westra, Ronald, Supervisor
Award date26 Nov 2015
Place of PublicationMaastricht
Publisher
Publication statusPublished - 2015

Keywords

  • mathematical method
  • links
  • atrial fibrillation

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