Intelligent Classifier for Atrial Fibrillation (ECG)
Created by W.Langdon from
gp-bibliography.bib Revision:1.7964
- @InCollection{DBLP:reference/ai/ValenzuelaRRGHRC09,
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author = "Olga Valenzuela and Ignacio Rojas and
Fernando Rojas and Alberto Guillen and Luis Javier Herrera and
Fernando J. Rojas and Maria {del Mar Cepero}",
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title = "Intelligent Classifier for Atrial Fibrillation
{(ECG)}",
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booktitle = "Encyclopedia of Artificial Intelligence",
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publisher = "IGI Global",
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year = "2009",
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editor = "Juan R. Rabunal and Julian Dorado and
Alejandro Pazos",
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chapter = "134",
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pages = "910--916",
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address = "Hershey, PA, USA",
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keywords = "genetic algorithms, genetic programming",
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timestamp = "Sun, 25 Jul 2021 11:43:38 +0200",
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biburl = "https://dblp.org/rec/reference/ai/ValenzuelaRRGHRC09.bib",
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bibsource = "dblp computer science bibliography, https://dblp.org",
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URL = "http://www.igi-global.com/Bookstore/Chapter.aspx?TitleId=10351",
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DOI = "doi:10.4018/978-1-59904-849-9.ch134",
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abstract = "This chapter is focused on the analysis and
classification of arrhythmias. An arrhythmia is any
cardiac pace that is not the typical sinusoidal one due
to alterations in the formation and/or transportation
of the impulses. In pathological conditions, the
depolarization process can be initiated outside the
sinoatrial (SA) node and several kinds of
extra-systolic or ectopic beatings can appear. Besides,
electrical impulses can be blocked, accelerated,
deviated by alternate trajectories and can change its
origin from one heart beat to the other, thus
originating several types of blockings and anomalous
connections. In both situations, changes in the signal
morphology or in the duration of its waves and
intervals can be produced on the ECG, as well as a lack
of one of the waves. This work is focused 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 that 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 realised. 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
mentioned before. A new method based on evolutionary
algorithms will be used to realise a selection of the
most relevant characteristics and to obtain a
classifier that will be capable of distinguishing the
different types of this pathology.",
- }
Genetic Programming entries for
Olga Valenzuela Cansino
Ignacio Rojas Ruiz
Fernando Rojas
Alberto Guillen Perales
Luis Javier Herrera Maldonado
Fernando Rojas Ruiz
Maria Del Mar Cepero Gonzalez
Citations