Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.11779/1954
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dc.contributor.authorGirişken, Yener-
dc.contributor.authorSon Turan, Semen-
dc.contributor.authorÇakar, Tuna-
dc.contributor.authorErtuğrul, Seyit-
dc.contributor.authorSayar, Alperen-
dc.date.accessioned2023-10-18T12:06:11Z
dc.date.available2023-10-18T12:06:11Z
dc.date.issued2023-
dc.identifier.citationÇakar, T., Son, S., Sayar, A., Girişken, Y., & Ertuğrul, S. (2023, July). Prediction of Loan Decisions with Optical Neuroimaging (fNIRS) and Machine Learning. In 2023 31st Signal Processing and Communications Applications Conference (SIU) (pp. 1-4). IEEE.en_US
dc.identifier.isbn9798350343557-
dc.identifier.issn2165-0608-
dc.identifier.urihttps://hdl.handle.net/20.500.11779/1954-
dc.identifier.urihttps://doi.org/10.1109/SIU59756.2023.10224010-
dc.description.abstractThe successful applications of neuroscientific methods and artificial learning approaches have increased in applied fields such as economics, marketing, and finance in the last decade. In this study, a prediction model was developed using the output of optical neuroimaging (fNIRS) measurements from the prefrontal brain regions while 40 participants made decisions for 35 credit offers. The aim was to predict participants' responses to credit offers using artificial learning methods based on four metrics obtained over time from the optical neuroimaging system. The findings of the study indicate that the first 6 seconds (prior to the response entry) are particularly critical. While the performance rate in the developed prediction models is found to be higher, especially in tree-based algorithms, this paper includes a performance comparison of 5 models specifically.en_US
dc.description.sponsorshipIEEE,TUBITAK BILGEM,Turkcellen_US
dc.language.isotren_US
dc.publisherIEEEen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectOptical brain imagingen_US
dc.subjectBrainen_US
dc.subjectMachine learningen_US
dc.subjectNeurofinanceen_US
dc.subjectCredit decisionen_US
dc.subjectNeuroscienceen_US
dc.subjectNeuroeconomicsen_US
dc.subjectNear-infrared spectroscopyen_US
dc.subjectFnirsen_US
dc.subjectDecision makingen_US
dc.titlePrediction of Loan Decisions With Optical Neuroimaging (fnirs) and Machine Learningen_US
dc.typeConference Objecten_US
dc.identifier.doi10.1109/SIU59756.2023.10224010-
dc.identifier.scopus2-s2.0-85173503260en_US
dc.description.woscitationindexConference Proceedings Citation Index - Science - Conference Proceedings Citation Index - Social Science & Humanities-
dc.description.WoSDocumentTypeProceedings Paper
dc.description.WoSInternationalCollaborationUluslararası işbirliği ile yapılmayan - HAYIRen_US
dc.description.WoSPublishedMonthEkimen_US
dc.description.WoSIndexDate2023en_US
dc.description.WoSYOKperiodYÖK - 2022-23en_US
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
dc.departmentİİSBF, İşletme Bölümüen_US
dc.relation.journal31st IEEE Conference on Signal Processing and Communications Applications (SIU) -- JUL 05-08, 2023 -- Istanbul Tech Univ, Ayazaga Campus, Istanbul, TURKEYen_US
dc.relation.journal2023 31st Signal Processing and Communications Applications Conference, Siuen_US
dc.identifier.wosWOS:001062571000221en_US
dc.institutionauthorSon Turan, Semen-
item.grantfulltextembargo_20400101-
item.fulltextWith Fulltext-
item.languageiso639-1tr-
item.openairetypeConference Object-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
item.cerifentitytypePublications-
crisitem.author.dept04.03. Department of Business Administration-
crisitem.author.dept02.02. Department of Computer Engineering-
Appears in Collections:İşletme Bölümü Koleksiyonu
Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection
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