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Aprendizaje no supervisado: aplicación en epilepsia

dc.contributor.authorMartínez-Toro, Gabriel Mauricio
dc.contributor.authorRico-Bautista, Dewar
dc.contributor.authorRomero-Riaño, Efrén
dc.contributor.authorRomero-Riaño, Paola Andrea
dc.date.accessioned2020-10-27T00:19:55Z
dc.date.available2020-10-27T00:19:55Z
dc.date.issued2019-12-01
dc.identifier.issn2539-2115
dc.identifier.issn1657-2831
dc.identifier.urihttp://hdl.handle.net/20.500.12749/8823
dc.description.abstractLa epilepsia es uno de los trastornos neurológicos comunes caracterizado por convulsiones recurrentes. El objetivo principal de este artículo es dar a conocer el análisis de los resultados presentados en las gráficas de simulación de los datos de entrenamiento. Los datos fueron recolectados mediante el sistema 10-20. El sistema "10-20" es un método reconocido internacionalmente, este describe la ubicación de electrodos en la cabeza para una prueba de EEG. Se muestran las diferencias obtenidas entre las pruebas generadas con las anomalías de los datos de prueba a partir de los datos de entrenamiento. Finalmente, se interpretan los resultados y se discute sobre la eficacia del procedimiento.
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dc.language.isoeng
dc.publisherUniversidad Autónoma de Bucaramanga UNAB
dc.relationhttps://revistas.unab.edu.co/index.php/rcc/article/view/3718/3155
dc.relationHttps://revistas.unab.edu.co/index.php/rcc/article/view/3718/3141
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dc.relation.urihttps://revistas.unab.edu.co/index.php/rcc/article/view/3718
dc.rightsDerechos de autor 2019 Revista Colombiana de Computación
dc.rights.urihttp://creativecommons.org/licenses/by-nc-sa/4.0/*
dc.sourceRevista Colombiana de Computación; Vol. 20 Núm. 2 (2019): Revista Colombiana de Computación; 20-27
dc.subjectEpilepsia
dc.subjectAprendizaje profundo
dc.subjectAprendizaje automático
dc.subjectAuto codificación
dc.titleAprendizaje no supervisado: aplicación en epilepsia
dc.title.translatedUnsupervised learning: application to epilepsy
dc.type.driverinfo:eu-repo/semantics/article
dc.type.localArtículospa
dc.type.coarhttp://purl.org/coar/resource_type/c_7a1f
dc.subject.keywordsEpilepsy
dc.subject.keywordsDeep learning
dc.subject.keywordsAutomatic learning
dc.subject.keywordsAuto-encoding
dc.identifier.instnameinstname:Universidad Autónoma de Bucaramanga UNAB
dc.type.hasversionInfo:eu-repo/semantics/publishedVersion
dc.rights.accessrightsinfo:eu-repo/semantics/openAccess
dc.identifier.repourlrepourl:https://repositorio.unbosque.edu.co
dc.description.abstractenglishEpilepsy is a neurological disorder characterized by recurrent seizures. The primary objective is to present an analysis of the results shown in the training data simulation charts. Data were collected by means of the 10-20 system. The “10–20” system is an internationally recognized method to describe and apply the location of scalp electrodes in the context of an EEG exam. It shows the differences obtained between the tests generated and the anomalies of the test data based on training data. Finally, the results are interpreted and the efficacy of the procedure is discussed.
dc.identifier.doi10.29375/25392115.3718
dc.type.redcolhttp://purl.org/redcol/resource_type/CJournalArticle
dc.rights.creativecommonsAttribution-NonCommercial-ShareAlike 4.0 International*


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