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Exploring the Multimodal Integration of VR and MRI biomarkers for Enhanced Early Detection of Mild Cognitive Impairment
| DC Field | Value | Language |
|---|---|---|
| dc.contributor.author | Park, Bogyeom | - |
| dc.contributor.author | Kim, Yuwon | - |
| dc.contributor.author | Park, Jinseok | - |
| dc.contributor.author | Choi, Hojin | - |
| dc.contributor.author | Kim, Seong-Eun | - |
| dc.contributor.author | Ryu, Hokyoung | - |
| dc.contributor.author | Seo, Kyoungwon | - |
| dc.date.accessioned | 2024-11-28T18:31:39Z | - |
| dc.date.available | 2024-11-28T18:31:39Z | - |
| dc.date.issued | 2024-05 | - |
| dc.identifier.issn | 0000-0000 | - |
| dc.identifier.uri | https://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/198007 | - |
| dc.description.abstract | Early 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.extent | 8 | - |
| dc.language | 영어 | - |
| dc.language.iso | ENG | - |
| dc.publisher | Association for Computing Machinery | - |
| dc.title | Exploring the Multimodal Integration of VR and MRI biomarkers for Enhanced Early Detection of Mild Cognitive Impairment | - |
| dc.type | Article | - |
| dc.identifier.doi | 10.1145/3613905.3651108 | - |
| dc.identifier.scopusid | 2-s2.0-85194195293 | - |
| dc.identifier.wosid | 001227587704070 | - |
| dc.identifier.bibliographicCitation | Conference on Human Factors in Computing Systems - Proceedings, pp 1 - 8 | - |
| dc.citation.title | Conference on Human Factors in Computing Systems - Proceedings | - |
| dc.citation.startPage | 1 | - |
| dc.citation.endPage | 8 | - |
| dc.type.docType | Proceedings Paper | - |
| dc.description.isOpenAccess | N | - |
| dc.description.journalRegisteredClass | scopus | - |
| dc.relation.journalResearchArea | Computer Science | - |
| dc.relation.journalWebOfScienceCategory | Computer Science, Cybernetics | - |
| dc.relation.journalWebOfScienceCategory | Computer Science, Interdisciplinary Applications | - |
| dc.relation.journalWebOfScienceCategory | Computer Science, Theory & Methods | - |
| dc.subject.keywordPlus | Biomarkers | - |
| dc.subject.keywordPlus | Brain | - |
| dc.subject.keywordPlus | Support vector machines | - |
| dc.subject.keywordPlus | Virtual reality | - |
| dc.subject.keywordAuthor | Biomarker | - |
| dc.subject.keywordAuthor | Magnetic resonance imaging | - |
| dc.subject.keywordAuthor | Mild cognitive impairment | - |
| dc.subject.keywordAuthor | Virtual reality | - |
| dc.identifier.url | https://dl.acm.org/doi/10.1145/3613905.3651108 | - |
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