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

doi:10.1093/europace/euy243

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 journal › Article › Academic › peer-review

Original language	English
Pages (from-to)	113-119
Number of pages	7
Journal	EP Europace
Volume	20
DOIs	https://doi.org/10.1093/europace/euy243
Publication status	Published - Nov 2018
Event	9th 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 2017 → 5 Dec 2017

Keywords

QT-interval
T-wave
Morphology
Long QT syndrome
Machine learning
INTERVAL
REGULARIZATION

Cite this

Hermans, B. J. M., Stoks, J., Bennis, F. C., Vink, A. S., Garde, A., Wilde, A. A. M., Pison, L., Postema, P. G., & Delhaas, T. (2018). Support vector machine-based assessment of the T-wave morphology improves long QT syndrome diagnosis. EP Europace, 20, 113-119. https://doi.org/10.1093/europace/euy243

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

keywords = "QT-interval, T-wave, Morphology, Long QT syndrome, Machine learning, INTERVAL, REGULARIZATION",

author = "Hermans, {Ben J. M.} and Job Stoks and Bennis, {Frank C.} and Vink, {Arja S.} and Ainara Garde and Wilde, {Arthur A. M.} and Laurent Pison and Postema, {Pieter G.} and Tammo Delhaas",

year = "2018",

month = nov

doi = "10.1093/europace/euy243",

language = "English",

volume = "20",

pages = "113--119",

journal = "EP Europace",

issn = "1099-5129",

publisher = "Oxford University Press",

note = "9th Theo Rossi di Montelera (TRM) Forum on Computer Simulation and Experimental Assessment of Cardiac Function : From Model to Clinical Outcome ; Conference date: 04-12-2017 Through 05-12-2017",

}

Support vector machine-based assessment of the T-wave morphology improves long QT syndrome diagnosis. / Hermans, Ben J. M.; Stoks, Job ; Bennis, Frank C.; Vink, Arja S.; Garde, Ainara; Wilde, Arthur A. M.; Pison, Laurent; Postema, Pieter G.; Delhaas, Tammo.

In: EP Europace, Vol. 20, 11.2018, p. 113-119.

Research output: Contribution to journal › Article › Academic › peer-review

TY - JOUR

T1 - Support vector machine-based assessment of the T-wave morphology improves long QT syndrome diagnosis

AU - Hermans, Ben J. M.

AU - Stoks, Job

AU - Bennis, Frank C.

AU - Vink, Arja S.

AU - Garde, Ainara

AU - Wilde, Arthur A. M.

AU - Pison, Laurent

AU - Postema, Pieter G.

AU - Delhaas, Tammo

PY - 2018/11

Y1 - 2018/11

KW - QT-interval

KW - T-wave

KW - Morphology

KW - Long QT syndrome

KW - Machine learning

KW - INTERVAL

KW - REGULARIZATION

U2 - 10.1093/europace/euy243

DO - 10.1093/europace/euy243

M3 - Article

VL - 20

SP - 113

EP - 119

JO - EP Europace

JF - EP Europace

SN - 1099-5129

T2 - 9th Theo Rossi di Montelera (TRM) Forum on Computer Simulation and Experimental Assessment of Cardiac Function

Y2 - 4 December 2017 through 5 December 2017

ER -

Access to Document

10.1093/europace/euy243