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Multi-Institutional Collaborative Research Using Ophthalmic Medical Image Data Standardized by Radiology Common Data Model (R-CDM)
| DC Field | Value | Language |
|---|---|---|
| dc.contributor.author | Park, ChulHyoung | - |
| dc.contributor.author | Park, Sang Jun | - |
| dc.contributor.author | Lee, Da Yun | - |
| dc.contributor.author | You, Seng Chan | - |
| dc.contributor.author | Lee, Kihwang | - |
| dc.contributor.author | Park, Woong | - |
| dc.date.accessioned | 2025-02-03T08:47:45Z | - |
| dc.date.available | 2025-02-03T08:47:45Z | - |
| dc.date.created | 2025-07-02 | - |
| dc.date.issued | 2024-01 | - |
| dc.identifier.issn | 0926-9630 | - |
| dc.identifier.uri | https://ir.ymlib.yonsei.ac.kr/handle/22282913/201871 | - |
| dc.description.abstract | Observational Medical Outcome Partners - Common Data Model (OMOP-CDM) is an international standard model for standardizing electronic medical record data. However, unstructured data such as medical image data which is beyond the scope of standardization by the current OMOP-CDM is difficult to be used in multi-institutional collaborative research. Therefore, we developed the Radiology-CDM (R-CDM) which standardizes medical imaging data. As a proof of concept, 737,500 Optical Coherence Tomography (OCT) data from two tertiary hospitals in South Korea is standardized in the form of R-CDM. The relationship between chronic disease and retinal thickness was analyzed by using the R-CDM. Central macular thickness and retinal nerve fiber layer (RNFL) thickness were significantly thinner in the patients with hypertension compared to the control cohort. It is meaningful in that multi-institutional collaborative research using medical image data and clinical data simultaneously can be conducted very efficiently. | - |
| dc.description.statementOfResponsibility | restriction | - |
| dc.language | English | - |
| dc.publisher | IOS Press | - |
| dc.relation.isPartOf | MEDINFO 2023 - THE FUTURE IS ACCESSIBLE | - |
| dc.relation.isPartOf | Studies in Health Technology and Informatics | - |
| dc.rights | CC BY-NC-ND 2.0 KR | - |
| dc.title | Multi-Institutional Collaborative Research Using Ophthalmic Medical Image Data Standardized by Radiology Common Data Model (R-CDM) | - |
| dc.type | Article | - |
| dc.contributor.college | College of Medicine (의과대학) | - |
| dc.contributor.department | Dept. of Biomedical Systems Informatics (의생명시스템정보학교실) | - |
| dc.contributor.googleauthor | Park, ChulHyoung | - |
| dc.contributor.googleauthor | Park, Sang Jun | - |
| dc.contributor.googleauthor | Lee, Da Yun | - |
| dc.contributor.googleauthor | You, Seng Chan | - |
| dc.contributor.googleauthor | Lee, Kihwang | - |
| dc.contributor.googleauthor | Park, Woong | - |
| dc.identifier.doi | 10.3233/SHTI230925 | - |
| dc.relation.journalcode | J02693 | - |
| dc.identifier.pmid | 38269763 | - |
| dc.subject.keyword | Medical imaging data | - |
| dc.subject.keyword | data standardization | - |
| dc.subject.keyword | ophthalmology | - |
| dc.contributor.alternativeName | You, Seng Chan | - |
| dc.contributor.affiliatedAuthor | You, Seng Chan | - |
| dc.identifier.scopusid | 2-s2.0-85183578823 | - |
| dc.identifier.wosid | 001281987600010 | - |
| dc.citation.volume | 310 | - |
| dc.citation.startPage | 48 | - |
| dc.citation.endPage | 52 | - |
| dc.identifier.bibliographicCitation | MEDINFO 2023 - THE FUTURE IS ACCESSIBLE, Vol.310 : 48-52, 2024-01 | - |
| dc.identifier.rimsid | 87419 | - |
| dc.type.rims | ART | - |
| dc.description.journalClass | 1 | - |
| dc.description.journalClass | 1 | - |
| dc.subject.keywordAuthor | Medical imaging data | - |
| dc.subject.keywordAuthor | data standardization | - |
| dc.subject.keywordAuthor | ophthalmology | - |
| dc.type.docType | Proceedings Paper | - |
| dc.description.isOpenAccess | Y | - |
| dc.description.journalRegisteredClass | scopus | - |
| dc.relation.journalWebOfScienceCategory | Computer Science, Artificial Intelligence | - |
| dc.relation.journalWebOfScienceCategory | Computer Science, Information Systems | - |
| dc.relation.journalWebOfScienceCategory | Computer Science, Interdisciplinary Applications | - |
| dc.relation.journalWebOfScienceCategory | Health Care Sciences & Services | - |
| dc.relation.journalWebOfScienceCategory | Engineering, Biomedical | - |
| dc.relation.journalWebOfScienceCategory | Medical Informatics | - |
| dc.relation.journalResearchArea | Computer Science | - |
| dc.relation.journalResearchArea | Health Care Sciences & Services | - |
| dc.relation.journalResearchArea | Engineering | - |
| dc.relation.journalResearchArea | Medical Informatics | - |
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