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dc.contributor.authorKeleş, Hasan Onur
dc.contributor.authorKarakulak, Ece Zeynep
dc.contributor.authorHanoğlu, Lütfü
dc.contributor.authorOmurtag, Ahmet
dc.date.accessioned2022-12-26T08:43:27Z
dc.date.available2022-12-26T08:43:27Z
dc.date.issued2022en_US
dc.identifier.citationKeleş, H. O., Karakulak, E. Z., Hanoğlu, L. ve Omurtag, A. (2022). Screening for Alzheimer's disease using prefrontal resting-state functional near-infrared spectroscopy. Frontiers in Human Neuroscience, 16. https://doi.org/10.3389/fnhum.2022.1061668en_US
dc.identifier.issn1662-5161
dc.identifier.urihttps://doi.org/10.3389/fnhum.2022.1061668
dc.identifier.urihttps://hdl.handle.net/20.500.12511/10182
dc.description.abstractIntroductionAlzheimer's disease (AD) is neurodegenerative dementia that causes neurovascular dysfunction and cognitive impairment. Currently, 50 million people live with dementia worldwide, and there are nearly 10 million new cases every year. There is a need for relatively less costly and more objective methods of screening and early diagnosis. MethodsFunctional near-infrared spectroscopy (fNIRS) systems are a promising solution for the early Detection of AD. For a practical clinically relevant system, a smaller number of optimally placed channels are clearly preferable. In this study, we investigated the number and locations of the best-performing fNIRS channels measuring prefrontal cortex activations. Twenty-one subjects diagnosed with AD and eighteen healthy controls were recruited for the study. ResultsWe have shown that resting-state fNIRS recordings from a small number of prefrontal locations provide a promising methodology for detecting AD and monitoring its progression. A high-density continuous-wave fNIRS system was first used to verify the relatively lower hemodynamic activity in the prefrontal cortical areas observed in patients with AD. By using the episode averaged standard deviation of the oxyhemoglobin concentration changes as features that were fed into a Support Vector Machine; we then showed that the accuracy of subsets of optical channels in predicting the presence and severity of AD was significantly above chance. The results suggest that AD can be detected with a 0.76 sensitivity score and a 0.68 specificity score while the severity of AD could be detected with a 0.75 sensitivity score and a 0.72 specificity score with <= 5 channels. DiscussionThese scores suggest that fNIRS is a viable technology for conveniently detecting and monitoring AD as well as investigating underlying mechanisms of disease progression.en_US
dc.language.isoengen_US
dc.publisherFrontiers Media S.A.en_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.rightsAttribution 4.0 International*
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/*
dc.subjectfNIRSen_US
dc.subjectCognitiveen_US
dc.subjectAlzheimer’s Diseaseen_US
dc.subjectMachine Learningen_US
dc.subjectEarly Diagnosisen_US
dc.titleScreening for Alzheimer's disease using prefrontal resting-state functional near-infrared spectroscopyen_US
dc.typearticleen_US
dc.relation.ispartofFrontiers in Human Neuroscienceen_US
dc.departmentİstanbul Medipol Üniversitesi, Tıp Fakültesi, Dahili Tıp Bilimleri Bölümü, Nöroloji Ana Bilim Dalıen_US
dc.authorid0000-0003-4292-5717en_US
dc.identifier.volume16en_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.identifier.doi10.3389/fnhum.2022.1061668en_US
dc.institutionauthorHanoğlu, Lütfü
dc.identifier.wosqualityQ2en_US
dc.identifier.wos000895972900001en_US
dc.identifier.scopus2-s2.0-85144036615en_US
dc.identifier.pmid36518566en_US
dc.identifier.scopusqualityQ2en_US


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