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dc.contributor.authorKhodabakhsh, Ali
dc.contributor.authorDemiroğlu, Cenk
dc.date.accessioned2016-02-15T13:38:34Z
dc.date.available2016-02-15T13:38:34Z
dc.date.issued2014
dc.identifier.isbn978-1-4939-1985-7
dc.identifier.urihttp://hdl.handle.net/10679/2380
dc.identifier.urihttp://link.springer.com/protocol/10.1007/978-1-4939-1985-7_11
dc.descriptionDue to copyright restrictions, the access to the full text of this article is only available via subscription.
dc.description.abstractAutomatic diagnosis of the Alzheimer’s disease as well as monitoring of the diagnosed patients can make significant economic impact on societies. We investigated an automatic diagnosis approach through the use of speech based features. As opposed to standard tests, spontaneous conversations are carried and recorded with the subjects. Speech features could discriminate between healthy people and the patients with high reliability. Although the patients were in later stages of Alzheimer’s disease, results indicate the potential of speech-based automated solutions for Alzheimer’s disease diagnosis. Moreover, the data collection process employed here can be done inexpensively by call center agents in a real-life application. Thus, the investigated techniques hold the potential to significantly reduce the financial burden on governments and Alzheimer’s patients.
dc.language.isoengen_US
dc.publisherSpringer Science+Business Media
dc.relation.ispartofData Mining in Clinical Medicine
dc.rightsrestrictedAccess
dc.titleAnalysis of speech-based measures for detecting and monitoring Alzheimer’s diseaseen_US
dc.typeBook chapteren_US
dc.peerreviewedyes
dc.publicationstatuspublisheden_US
dc.contributor.departmentÖzyeğin University
dc.contributor.authorID(ORCID 0000-0002-6160-3169 & YÖK ID 144947) Demiroğlu, Cenk
dc.contributor.ozuauthorDemiroğlu, Cenk
dc.identifier.volume1246
dc.identifier.startpage159
dc.identifier.endpage173
dc.identifier.doi10.1007/978-1-4939-1985-7_11
dc.subject.keywordsAlzheimer’s disease
dc.subject.keywordsSpeech analysis
dc.subject.keywordsSupport vector machines
dc.identifier.scopusSCOPUS:2-s2.0-84954581087
dc.contributor.ozugradstudentKhodabakhsh, Ali
dc.contributor.authorMale2
dc.relation.publicationcategoryBook Chapter - International - Institutional Academic Staff and Graduate Student


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