Please use this identifier to cite or link to this item: http://hdl.handle.net/10553/54996
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dc.contributor.authorCabrera-León, Ylermien_US
dc.contributor.authorGarcía Báez, Patricioen_US
dc.contributor.authorRuiz Alzola, Juanen_US
dc.contributor.authorSuárez-Araujo, Carmen Pazen_US
dc.date.accessioned2019-02-18T16:03:57Z-
dc.date.available2019-02-18T16:03:57Z-
dc.date.issued2018en_US
dc.identifier.isbn978-1-5386-1122-7en_US
dc.identifier.issn1562-5850en_US
dc.identifier.otherWoS-
dc.identifier.urihttp://hdl.handle.net/10553/54996-
dc.description.abstractThe elderly population in developed countries has augmented in the last decades. This has also entailed an increased prevalence of aging diseases. Mild Cognitive Impairment (MCI) is considered a prodromal stage of Alzheimer's Disease (AD), which is the most common dementia. We present a benchmarking of Machine Learning (ML) methods for MCI staging and its early detection via the multiclass classification of Cognitively Normal (CN), Early Mild Cognitive Impairment (EMCI) and Late Mild Cognitive Impairment (LMCI) subjects by means of neuropsychological scales. Data were obtained from Alzheimer's Disease Neuroimaging Initiative (ADNI). Our study has been aimed towards hybrid neural architectures, such as the Counter-propagation Network (CPN), for their input space quantification capability, and non-neural methods including ensembles. We also analyzed how class balancing affected them. Non-neural ensembles of learners obtained Area Under the Curve (AUC) values in the range 0.721-0.775, whereas 0.650-0.657 with the monolithic architecture CPN. This suggests that there is a weak difference among these cognitive stages, that the used scales do not offer high enough discriminant power, and that neural ensembles can be a more appropriate solution.en_US
dc.languageengen_US
dc.relationPlataforma E-Salud Traslacional de Ayuda Al Diagnóstico y Manejo de Enfermedades No Comunicables Asociadas Al Envejecimiento.en_US
dc.sourceINES 2018 - IEEE 22nd International Conference on Intelligent Engineering Systems, Proceedings (8523858), June 21-23, 2018, Las Palmas de Gran Canaria, Spain, p. 67-72en_US
dc.subject3201 Ciencias clínicasen_US
dc.subject120304 Inteligencia artificialen_US
dc.titleClassification of mild cognitive impairment stages using machine learning methodsen_US
dc.typeinfo:eu-repo/semantics/conferenceObjecten_US
dc.typeConferenceObjecten_US
dc.relation.conference22nd IEEE International Conference on Intelligent Engineering Systems, INES 2018en_US
dc.identifier.doi10.1109/INES.2018.8523858en_US
dc.identifier.scopus85058051123-
dc.identifier.isi000517754600013-
dc.contributor.orcid#NODATA#-
dc.contributor.orcid#NODATA#-
dc.contributor.orcid#NODATA#-
dc.contributor.orcid#NODATA#-
dc.contributor.authorscopusid57192423564-
dc.contributor.authorscopusid23476362100-
dc.contributor.authorscopusid56614041800-
dc.contributor.authorscopusid6603605708-
dc.description.lastpage000072en_US
dc.identifier.issue8523858-
dc.description.firstpage000067en_US
dc.investigacionIngeniería y Arquitecturaen_US
dc.type2Actas de congresosen_US
dc.contributor.daisngidNo ID-
dc.contributor.daisngidNo ID-
dc.contributor.daisngidNo ID-
dc.contributor.daisngidNo ID-
dc.description.numberofpages6en_US
dc.identifier.eisbn978-1-5386-1122-7-
dc.utils.revisionen_US
dc.contributor.wosstandardWOS:Cabrera-Leon, Y-
dc.contributor.wosstandardWOS:Baez, PG-
dc.contributor.wosstandardWOS:Ruiz-Alzola, J-
dc.contributor.wosstandardWOS:Suarez-Araujo, CP-
dc.date.coverdate2018en_US
dc.identifier.conferenceidevents121186-
dc.identifier.ulpgces
item.fulltextSin texto completo-
item.grantfulltextnone-
crisitem.author.deptTecnología Médica y Audiovisual-
crisitem.author.deptIU de Investigaciones Biomédicas y Sanitarias-
crisitem.author.deptDepartamento de Señales y Comunicaciones-
crisitem.author.deptIUCTC: Computación inteligente, percepción y big data-
crisitem.author.deptIU de Ciencias y Tecnologías Cibernéticas-
crisitem.author.deptDepartamento de Informática y Sistemas-
crisitem.author.orcid0000-0001-5709-2274-
crisitem.author.orcid0000-0002-3545-2328-
crisitem.author.orcid0000-0002-8826-0899-
crisitem.author.parentorgIU de Investigaciones Biomédicas y Sanitarias-
crisitem.author.parentorgIU de Ciencias y Tecnologías Cibernéticas-
crisitem.author.fullNameCabrera León, Ylermi-
crisitem.author.fullNameGarcía Báez, Patricio-
crisitem.author.fullNameRuiz Alzola, Juan Bautista-
crisitem.author.fullNameSuárez Araujo, Carmen Paz-
crisitem.event.eventsstartdate21-06-2018-
crisitem.event.eventsenddate23-06-2018-
Appears in Collections:Actas de congresos
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