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Neural Networks in ECG Classification: What is Next for Adaptive Systems?

Neural Networks in ECG Classification: What is Next for Adaptive Systems?

G. Camps-Valls, J. F. Guerrero-Martinez
Copyright: © 2006 |Pages: 24
ISBN13: 9781591408482|ISBN10: 1591408482|EISBN13: 9781591408505
DOI: 10.4018/978-1-59140-848-2.ch004
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MLA

Camps-Valls, G., and J. F. Guerrero-Martinez. "Neural Networks in ECG Classification: What is Next for Adaptive Systems?." Neural Networks in Healthcare: Potential and Challenges, edited by Rezaul Begg, et al., IGI Global, 2006, pp. 81-104. https://doi.org/10.4018/978-1-59140-848-2.ch004

APA

Camps-Valls, G. & Guerrero-Martinez, J. F. (2006). Neural Networks in ECG Classification: What is Next for Adaptive Systems?. In R. Begg, J. Kamruzzaman, & R. Sarker (Eds.), Neural Networks in Healthcare: Potential and Challenges (pp. 81-104). IGI Global. https://doi.org/10.4018/978-1-59140-848-2.ch004

Chicago

Camps-Valls, G., and J. F. Guerrero-Martinez. "Neural Networks in ECG Classification: What is Next for Adaptive Systems?." In Neural Networks in Healthcare: Potential and Challenges, edited by Rezaul Begg, Joarder Kamruzzaman, and Ruhul Sarker, 81-104. Hershey, PA: IGI Global, 2006. https://doi.org/10.4018/978-1-59140-848-2.ch004

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Abstract

In this chapter, we review the vast field of application of artificial neural networks in cardiac pathology discrimination based on electrocardiographic signals. We discuss advantages and drawbacks of neural and adaptive systems in cardiovascular medicine and catch a glimpse of forthcoming developments in machine learning models for the real clinical environment. Some problems are identified in the learning tasks of beat detection, feature selection/extraction, and classification, and some proposals and suggestions are given to alleviate the problems of interpretability, overfitting, and adaptation. These have become important problems in recent years and will surely constitute the basis of some investigations in the immediate future.

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