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Multi-Institutional Collaborative Research Using Ophthalmic Medical Image Data Standardized by Radiology Common Data Model (R-CDM)

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dc.contributor.authorPark, ChulHyoung-
dc.contributor.authorPark, Sang Jun-
dc.contributor.authorLee, Da Yun-
dc.contributor.authorYou, Seng Chan-
dc.contributor.authorLee, Kihwang-
dc.contributor.authorPark, Woong-
dc.date.accessioned2025-02-03T08:47:45Z-
dc.date.available2025-02-03T08:47:45Z-
dc.date.created2025-07-02-
dc.date.issued2024-01-
dc.identifier.issn0926-9630-
dc.identifier.urihttps://ir.ymlib.yonsei.ac.kr/handle/22282913/201871-
dc.description.abstractObservational 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.statementOfResponsibilityrestriction-
dc.languageEnglish-
dc.publisherIOS Press-
dc.relation.isPartOfMEDINFO 2023 - THE FUTURE IS ACCESSIBLE-
dc.relation.isPartOfStudies in Health Technology and Informatics-
dc.rightsCC BY-NC-ND 2.0 KR-
dc.titleMulti-Institutional Collaborative Research Using Ophthalmic Medical Image Data Standardized by Radiology Common Data Model (R-CDM)-
dc.typeArticle-
dc.contributor.collegeCollege of Medicine (의과대학)-
dc.contributor.departmentDept. of Biomedical Systems Informatics (의생명시스템정보학교실)-
dc.contributor.googleauthorPark, ChulHyoung-
dc.contributor.googleauthorPark, Sang Jun-
dc.contributor.googleauthorLee, Da Yun-
dc.contributor.googleauthorYou, Seng Chan-
dc.contributor.googleauthorLee, Kihwang-
dc.contributor.googleauthorPark, Woong-
dc.identifier.doi10.3233/SHTI230925-
dc.relation.journalcodeJ02693-
dc.identifier.pmid38269763-
dc.subject.keywordMedical imaging data-
dc.subject.keyworddata standardization-
dc.subject.keywordophthalmology-
dc.contributor.alternativeNameYou, Seng Chan-
dc.contributor.affiliatedAuthorYou, Seng Chan-
dc.identifier.scopusid2-s2.0-85183578823-
dc.identifier.wosid001281987600010-
dc.citation.volume310-
dc.citation.startPage48-
dc.citation.endPage52-
dc.identifier.bibliographicCitationMEDINFO 2023 - THE FUTURE IS ACCESSIBLE, Vol.310 : 48-52, 2024-01-
dc.identifier.rimsid87419-
dc.type.rimsART-
dc.description.journalClass1-
dc.description.journalClass1-
dc.subject.keywordAuthorMedical imaging data-
dc.subject.keywordAuthordata standardization-
dc.subject.keywordAuthorophthalmology-
dc.type.docTypeProceedings Paper-
dc.description.isOpenAccessY-
dc.description.journalRegisteredClassscopus-
dc.relation.journalWebOfScienceCategoryComputer Science, Artificial Intelligence-
dc.relation.journalWebOfScienceCategoryComputer Science, Information Systems-
dc.relation.journalWebOfScienceCategoryComputer Science, Interdisciplinary Applications-
dc.relation.journalWebOfScienceCategoryHealth Care Sciences & Services-
dc.relation.journalWebOfScienceCategoryEngineering, Biomedical-
dc.relation.journalWebOfScienceCategoryMedical Informatics-
dc.relation.journalResearchAreaComputer Science-
dc.relation.journalResearchAreaHealth Care Sciences & Services-
dc.relation.journalResearchAreaEngineering-
dc.relation.journalResearchAreaMedical Informatics-
Appears in Collections:
1. College of Medicine (의과대학) > Dept. of Biomedical Systems Informatics (의생명시스템정보학교실) > 1. Journal Papers

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