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Exploring the Multimodal Integration of VR and MRI biomarkers for Enhanced Early Detection of Mild Cognitive Impairment

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dc.contributor.authorPark, Bogyeom-
dc.contributor.authorKim, Yuwon-
dc.contributor.authorPark, Jinseok-
dc.contributor.authorChoi, Hojin-
dc.contributor.authorKim, Seong-Eun-
dc.contributor.authorRyu, Hokyoung-
dc.contributor.authorSeo, Kyoungwon-
dc.date.accessioned2024-11-28T18:31:39Z-
dc.date.available2024-11-28T18:31:39Z-
dc.date.issued2024-05-
dc.identifier.issn0000-0000-
dc.identifier.urihttps://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/198007-
dc.description.abstractEarly detection of mild cognitive impairment (MCI) is crucial to impede dementia progression. Virtual reality (VR) biomarkers are adept at detecting impairments in instrumental activities of daily living (IADL), whereas magnetic resonance imaging (MRI) biomarkers excel in measuring observable structural changes in the brain. However, the efficacy of integrating VR and MRI biomarkers to improve early MCI detection remains unclear. This study aims to evaluate and compare the effectiveness of VR and MRI biomarkers and investigates the potential of their combined use for more accurate early MCI detection. Through support vector machine analysis, distinct characteristics were observed. For identifying MCI, VR biomarkers demonstrated high specificity (90.0%), whereas MRI showed high sensitivity (90.9%). The combination of both biomarkers yielded superior results in accuracy (94.4%), sensitivity (100.0%), and specificity (90.9%). Drawing from these results, we suggest a sequential diagnostic approach, employing VR for initial screening and MRI for subsequent confirmation of MCI.-
dc.format.extent8-
dc.language영어-
dc.language.isoENG-
dc.publisherAssociation for Computing Machinery-
dc.titleExploring the Multimodal Integration of VR and MRI biomarkers for Enhanced Early Detection of Mild Cognitive Impairment-
dc.typeArticle-
dc.identifier.doi10.1145/3613905.3651108-
dc.identifier.scopusid2-s2.0-85194195293-
dc.identifier.wosid001227587704070-
dc.identifier.bibliographicCitationConference on Human Factors in Computing Systems - Proceedings, pp 1 - 8-
dc.citation.titleConference on Human Factors in Computing Systems - Proceedings-
dc.citation.startPage1-
dc.citation.endPage8-
dc.type.docTypeProceedings Paper-
dc.description.isOpenAccessN-
dc.description.journalRegisteredClassscopus-
dc.relation.journalResearchAreaComputer Science-
dc.relation.journalWebOfScienceCategoryComputer Science, Cybernetics-
dc.relation.journalWebOfScienceCategoryComputer Science, Interdisciplinary Applications-
dc.relation.journalWebOfScienceCategoryComputer Science, Theory & Methods-
dc.subject.keywordPlusBiomarkers-
dc.subject.keywordPlusBrain-
dc.subject.keywordPlusSupport vector machines-
dc.subject.keywordPlusVirtual reality-
dc.subject.keywordAuthorBiomarker-
dc.subject.keywordAuthorMagnetic resonance imaging-
dc.subject.keywordAuthorMild cognitive impairment-
dc.subject.keywordAuthorVirtual reality-
dc.identifier.urlhttps://dl.acm.org/doi/10.1145/3613905.3651108-
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서울 의과대학 > 서울 신경과학교실 > 1. Journal Articles
서울 기술경영전문대학원 > 서울 기술경영학과 > 1. Journal Articles

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