Support vector machine-based assessment of the T-wave morphology improves long QT syndrome diagnosis

Ben J. M. Hermans, Job Stoks, Frank C. Bennis, Arja S. Vink, Ainara Garde, Arthur A. M. Wilde, Laurent Pison, Pieter G. Postema, Tammo Delhaas*

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

Original languageEnglish
Pages (from-to)113-119
Number of pages7
JournalEP Europace
Publication statusPublished - Nov 2018
Event9th Theo Rossi di Montelera (TRM) Forum on Computer Simulation and Experimental Assessment of Cardiac Function: From Model to Clinical Outcome - Ctr Computat Med Cardiol, Lugano, SWITZERLAND, Lugano, Switzerland
Duration: 4 Dec 20175 Dec 2017


  • QT-interval
  • T-wave
  • Morphology
  • Long QT syndrome
  • Machine learning

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