Assessing common classification methods for the identification of abnormal repolarization using indicators of T-wave morphology and QT interval

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Standard

Assessing common classification methods for the identification of abnormal repolarization using indicators of T-wave morphology and QT interval. / Shakibfar, Saeed; Graff, Claus; Ehlers, Lars Holger; Toft, Egon; Kanters, Jørgen K.; Struijk, Johannes J.

In: Computers in Biology and Medicine, Vol. 42, No. 4, 04.2012, p. 485-91.

Research output: Contribution to journal › Journal article › Research › peer-review

Harvard

Shakibfar, S, Graff, C, Ehlers, LH, Toft, E, Kanters, JK & Struijk, JJ 2012, 'Assessing common classification methods for the identification of abnormal repolarization using indicators of T-wave morphology and QT interval', Computers in Biology and Medicine, vol. 42, no. 4, pp. 485-91. https://doi.org/10.1016/j.compbiomed.2012.01.001

APA

Shakibfar, S., Graff, C., Ehlers, L. H., Toft, E., Kanters, J. K., & Struijk, J. J. (2012). Assessing common classification methods for the identification of abnormal repolarization using indicators of T-wave morphology and QT interval. Computers in Biology and Medicine, 42(4), 485-91. https://doi.org/10.1016/j.compbiomed.2012.01.001

Vancouver

Shakibfar S, Graff C, Ehlers LH, Toft E, Kanters JK, Struijk JJ. Assessing common classification methods for the identification of abnormal repolarization using indicators of T-wave morphology and QT interval. Computers in Biology and Medicine. 2012 Apr;42(4):485-91. https://doi.org/10.1016/j.compbiomed.2012.01.001

Author

Shakibfar, Saeed ; Graff, Claus ; Ehlers, Lars Holger ; Toft, Egon ; Kanters, Jørgen K. ; Struijk, Johannes J. / Assessing common classification methods for the identification of abnormal repolarization using indicators of T-wave morphology and QT interval. In: Computers in Biology and Medicine. 2012 ; Vol. 42, No. 4. pp. 485-91.

Bibtex

@article{6b7b78c4c5dc4ae18472af0d2df7913e,

title = "Assessing common classification methods for the identification of abnormal repolarization using indicators of T-wave morphology and QT interval",

abstract = "Various parameters based on QTc and T-wave morphology have been shown to be useful discriminators for drug induced I(Kr)-blocking. Using different classification methods this study compares the potential of these two features for identifying abnormal repolarization on the ECG. A group of healthy volunteers and LQT2 carriers were used to train classification algorithms using measures of T-wave morphology and QTc. The ability to correctly classify a third group of test subjects before and after receiving d,l-sotalol was evaluated using classification rules derived from training. As a single electrocardiographic feature, T-wave morphology separates normal from abnormal repolarization better than QTc. It is further indicated that nonlinear boundaries can provide stronger classifiers than a linear boundaries. Whether this is true in general with other ECG markers and other data sets is uncertain because the approach has not been tested in this setting.",

keywords = "Adult, Algorithms, Cluster Analysis, Discriminant Analysis, Electrocardiography, Female, Fuzzy Logic, Humans, Long QT Syndrome, Male, Multivariate Analysis, ROC Curve, Signal Processing, Computer-Assisted",

author = "Saeed Shakibfar and Claus Graff and Ehlers, {Lars Holger} and Egon Toft and Kanters, {J{\o}rgen K.} and Struijk, {Johannes J.}",

year = "2012",

month = apr,

doi = "10.1016/j.compbiomed.2012.01.001",

language = "English",

volume = "42",

pages = "485--91",

journal = "Computers in Biology and Medicine",

issn = "0010-4825",

publisher = "Pergamon Press",

number = "4",

}

RIS

TY - JOUR

T1 - Assessing common classification methods for the identification of abnormal repolarization using indicators of T-wave morphology and QT interval

AU - Shakibfar, Saeed

AU - Graff, Claus

AU - Ehlers, Lars Holger

AU - Toft, Egon

AU - Kanters, Jørgen K.

AU - Struijk, Johannes J.

PY - 2012/4

Y1 - 2012/4

N2 - Various parameters based on QTc and T-wave morphology have been shown to be useful discriminators for drug induced I(Kr)-blocking. Using different classification methods this study compares the potential of these two features for identifying abnormal repolarization on the ECG. A group of healthy volunteers and LQT2 carriers were used to train classification algorithms using measures of T-wave morphology and QTc. The ability to correctly classify a third group of test subjects before and after receiving d,l-sotalol was evaluated using classification rules derived from training. As a single electrocardiographic feature, T-wave morphology separates normal from abnormal repolarization better than QTc. It is further indicated that nonlinear boundaries can provide stronger classifiers than a linear boundaries. Whether this is true in general with other ECG markers and other data sets is uncertain because the approach has not been tested in this setting.

AB - Various parameters based on QTc and T-wave morphology have been shown to be useful discriminators for drug induced I(Kr)-blocking. Using different classification methods this study compares the potential of these two features for identifying abnormal repolarization on the ECG. A group of healthy volunteers and LQT2 carriers were used to train classification algorithms using measures of T-wave morphology and QTc. The ability to correctly classify a third group of test subjects before and after receiving d,l-sotalol was evaluated using classification rules derived from training. As a single electrocardiographic feature, T-wave morphology separates normal from abnormal repolarization better than QTc. It is further indicated that nonlinear boundaries can provide stronger classifiers than a linear boundaries. Whether this is true in general with other ECG markers and other data sets is uncertain because the approach has not been tested in this setting.

KW - Adult

KW - Algorithms

KW - Cluster Analysis

KW - Discriminant Analysis

KW - Electrocardiography

KW - Female

KW - Fuzzy Logic

KW - Humans

KW - Long QT Syndrome

KW - Male

KW - Multivariate Analysis

KW - ROC Curve

KW - Signal Processing, Computer-Assisted

U2 - 10.1016/j.compbiomed.2012.01.001

DO - 10.1016/j.compbiomed.2012.01.001

M3 - Journal article

C2 - 22306238

VL - 42

SP - 485

EP - 491

JO - Computers in Biology and Medicine

JF - Computers in Biology and Medicine

SN - 0010-4825

IS - 4

ER -

ID: 48052437

Department of Biomedical Sciences