@misc{10481/77909,
year = {2009},
month = {11},
url = {https://hdl.handle.net/10481/77909},
abstract = {This article focuses on the development of intelligent classifiers in the area of biomedicine,
focusing on the problem of diagnosing cardiac diseases based on the electrocardiogram (ECG),
or more precisely, on the differentiation of the types of atrial fibrillations. First of all, we will
study the ECG, and the treatment of the ECG in order to work with it with this specific
pathology. In order to achieve this we will study different ways of elimination, in the best
possible way, of any activity that is not caused by the auriculars. We will study and imitate
the ECG treatment methodologies and the characteristics extracted from the electrocardiograms
that were used by the researchers who obtained the best results in the Physionet Challenge, where
the classification of ECG recordings according to the type of atrial fibrillation (AF) that they
showed, was realized. We will extract a great amount of characteristics, partly those used by these
researchers and additional characteristics that we consider to be important for the distinction
previously mentioned. A new method based on evolutionary algorithms will be used to realize
a selection of the most relevant characteristics and to obtain a classifier that will be capable of
distinguishing the different types of this pathology.},
publisher = {Taylor & Francis},
keywords = {Inteligencia artificial},
keywords = {Artificial intelligence},
title = {Intelligent system based on genetic programming for atrial fibrillation classification},
doi = {10.1080/08839510903363420},
author = {Valenzuela Cansino, Olga and Rojas Ruiz, Ignacio and Rojas Ruiz, Francisco Javier and Pomares Cintas, Héctor Emilio and Bernier Villamor, José Luis and Herrera Maldonado, Luis Javier and Guillén Perales, Alberto},
}