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

作者：Shakibfar Saeed^*; Graff Claus; Ehlers Lars H; Toft Egon; Kanters Jorgen K; Struijk Johannes J

来源：Computers in Biology and Medicine, 2012, 42(4): 485-491.

DOI：10.1016/j.compbiomed.2012.01.001

• Discriminant analysis
• Fuzzy clustering
• T-wave morphology
• QT interval
• Long QT syndrome

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.

• 出版日期2012-4