Abstract
The QT interval measured on the body-surface Electrocardiogram (ECG), corresponds to the time elapsed between the depolarization of the first myocardial ventricular cell (beginning of the Q wave) and the end of the repolarisation of the last ventricular cell (end of the T wave). Predictive models of the QT dynamical behavior are believed to be a useful tool to detect abnormalities in QT adaptation for heart rate changes. In this paper, patient specific predictive models based on a Multi Layer Perceptrons are presented and their predictive performances are tested on real and artificial data.
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© 2001 Springer-Verlag Berlin Heidelberg
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El Dajani, R., Miquel, M., Forlini, MC., Rubel, P. (2001). Modeling of Ventricular Repolarisation Time Series by Multi-Layer Perceptrons. In: Quaglini, S., Barahona, P., Andreassen, S. (eds) Artificial Intelligence in Medicine. AIME 2001. Lecture Notes in Computer Science(), vol 2101. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-48229-6_23
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DOI: https://doi.org/10.1007/3-540-48229-6_23
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