Application of machine learning techniques to analyse the effects of physical exercise in ventricular fibrillation
NAGIOS: RODERIC FUNCIONANDO

Application of machine learning techniques to analyse the effects of physical exercise in ventricular fibrillation

DSpace Repository

Application of machine learning techniques to analyse the effects of physical exercise in ventricular fibrillation

Show simple item record

dc.contributor.author Caravaca Moreno, Juan
dc.contributor.author Soria Olivas, Emilio
dc.contributor.author Bataller Mompean, Manuel
dc.contributor.author Serrano López, Antonio José
dc.contributor.author Such Miquel, Luis
dc.contributor.author Vila Francés, Joan
dc.contributor.author Guerrero Martínez, Juan Francisco
dc.date.accessioned 2015-03-02T12:09:20Z
dc.date.available 2015-03-02T12:09:20Z
dc.date.issued 2014
dc.identifier.uri http://hdl.handle.net/10550/42558
dc.description.abstract This work presents the application of machine learning techniques to analyze the influence of physical exercise in the heart's physiological properties, during ventricular fibrillation. With that purpose, different kinds of classifiers (linear and neural models) were used to classify between trained and sedentary rabbit hearts. These classifiers were used to perform knowledge extraction through a wrapper feature selection algorithm. The obtained results showed the higher performance of the neural models compared to the linear classifier (higher performance measures and higher dimensionality reduction). The most relevant features to describe the benefits of physical exercise are those related to myocardial heterogeneity, mean activation rate and activation complexity.
dc.language.iso eng
dc.relation.ispartof Computers in Biology and Medicine, 2014, vol. 45, num. 1, p. 1-7
dc.rights.uri info:eu-repo/semantics/openAccess
dc.source Caravaca Moreno, Juan Soria Olivas, Emilio Bataller Mompeán, Manuel Serrano López, Antonio J. Such Miquel, Luis Vila Francés, Joan Guerrero Martínez, Juan Francisco 2014 Application of machine learning techniques to analyse the effects of physical exercise in ventricular fibrillation Computers in Biology and Medicine 45 1 1 7
dc.subject Cor Malalties
dc.subject Enginyeria biomèdica
dc.title Application of machine learning techniques to analyse the effects of physical exercise in ventricular fibrillation
dc.type info:eu-repo/semantics/article
dc.date.updated 2015-03-02T12:09:20Z
dc.identifier.doi http://dx.doi.org/10.1016/j.compbiomed.2013.11.008
dc.identifier.idgrec 093255

View       (480.9Kb)

This item appears in the following Collection(s)

Show simple item record

Search DSpace

Advanced Search

Browse

Statistics