Please use this identifier to cite or link to this item: http://hdl.handle.net/10553/72591
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dc.contributor.authorGarcía Báez, Patricioen_US
dc.contributor.authorSuárez Araujo, Carmen Pazen_US
dc.contributor.authorFernández Viadero,Carlosen_US
dc.contributor.authorRegidor García,Joséen_US
dc.date.accessioned2020-05-19T12:09:42Z-
dc.date.available2020-05-19T12:09:42Z-
dc.date.issued2007en_US
dc.identifier.isbn978-3-540-77225-5en_US
dc.identifier.issn0302-9743en_US
dc.identifier.otherWoS-
dc.identifier.urihttp://hdl.handle.net/10553/72591-
dc.description.abstractThis work tries to go a step further in the development of methods based on automatic learning techniques to parse and interpret data relating to cognitive decline (CD). There have been studied the neuropsychological tests of 267 consultations made over 30 patients by the Alzheimer's Patient Association of Gran Canaria in 2005. The Sanger neural network adaptation for missing values treatment has allowed making a Principal Components Analysis (PCA) on the successfully obtained data. The results show that the first three obtained principal components are able to extract information relating to functional, cognitive and instrumental sintomatology, respectively, from the test. By means of these techniques, it is possible to develop tools that allow physicians to quantify, view and make a better pursuit of the sintomatology associated to the cognitive decline processes, contributing to a better knowledge of these ones.en_US
dc.languageengen_US
dc.relationHacia Un Prototipo de Sistema Computacional de Inteligente de Ayuda Al Diagnóstico Del Deterioro Cognitivo Leve (Dcl) y de la Enfermedad de Alzheimer y Otras Demencias.en_US
dc.relation.ispartofLecture Notes in Computer Scienceen_US
dc.sourceYin H., Tino P., Corchado E., Byrne W., Yao X. (eds) Intelligent Data Engineering and Automated Learning - IDEAL 2007. Lecture Notes in Computer Science, [ISSN 0302-9743], vol 4881, p. 898-907, (2007). Springer, Berlin, Heidelberg.en_US
dc.subject120304 Inteligencia artificialen_US
dc.subject3201 Ciencias clínicasen_US
dc.titleAutomatic prognostic determination and evolution of cognitive decline using artificial neural networksen_US
dc.typeinfo:eu-repo/semantics/conferenceObjecten_US
dc.typeConferenceObjecten_US
dc.relation.conference8th International Conference on Intelligent Data Engineering and Automated Learningen_US
dc.identifier.doi10.1007/978-3-540-77226-2_90en_US
dc.identifier.scopus38549116066-
dc.identifier.isi000252394900090-
dc.contributor.authorscopusid23476362100-
dc.contributor.authorscopusid23476354000-
dc.contributor.authorscopusid57188767199-
dc.contributor.authorscopusid57206752700-
dc.identifier.eissn1611-3349-
dc.description.lastpage907en_US
dc.description.firstpage898en_US
dc.relation.volume4881en_US
dc.investigacionIngeniería y Arquitecturaen_US
dc.type2Actas de congresosen_US
dc.contributor.daisngid2362390-
dc.contributor.daisngid1776211-
dc.contributor.daisngid4763008-
dc.contributor.daisngid7101677-
dc.description.numberofpages3en_US
dc.identifier.eisbn978-3-540-77226-2-
dc.utils.revisionen_US
dc.contributor.wosstandardWOS:Baez, PG-
dc.contributor.wosstandardWOS:Araujo, CPS-
dc.contributor.wosstandardWOS:Viadero, CF-
dc.contributor.wosstandardWOS:Garcia, JR-
dc.date.coverdateDiciembre 2007en_US
dc.identifier.conferenceidevents120597-
dc.identifier.ulpgces
item.grantfulltextnone-
item.fulltextSin texto completo-
crisitem.author.deptIUCTC: Computación inteligente, percepción y big data-
crisitem.author.deptIU de Ciencias y Tecnologías Cibernéticas-
crisitem.author.deptInformática y Sistemas-
crisitem.author.orcid0000-0002-8826-0899-
crisitem.author.parentorgIU de Ciencias y Tecnologías Cibernéticas-
crisitem.author.fullNameGarcía Báez, Patricio-
crisitem.author.fullNameSuárez Araujo, Carmen Paz-
crisitem.author.fullNameFernández Viadero,Carlos-
crisitem.author.fullNameRegidor García,José-
crisitem.event.eventsstartdate16-12-2007-
crisitem.event.eventsenddate19-12-2007-
Appears in Collections:Actas de congresos
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