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Development of Medical Imaging Data Standardization for Imaging-Based Observational Research: OMOP Common Data Model Extension

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dc.contributor.author유승찬-
dc.date.accessioned2024-06-14T03:02:37Z-
dc.date.available2024-06-14T03:02:37Z-
dc.date.issued2024-04-
dc.identifier.issn2948-2925-
dc.identifier.urihttps://ir.ymlib.yonsei.ac.kr/handle/22282913/199775-
dc.description.abstractThe rapid growth of artificial intelligence (AI) and deep learning techniques require access to large inter-institutional cohorts of data to enable the development of robust models, e.g., targeting the identification of disease biomarkers and quantifying disease progression and treatment efficacy. The Observational Medical Outcomes Partnership Common Data Model (OMOP CDM) has been designed to accommodate a harmonized representation of observational healthcare data. This study proposes the Medical Imaging CDM (MI-CDM) extension, adding two new tables and two vocabularies to the OMOP CDM to address the structural and semantic requirements to support imaging research. The tables provide the capabilities of linking DICOM data sources as well as tracking the provenance of imaging features derived from those images. The implementation of the extension enables phenotype definitions using imaging features and expanding standardized computable imaging biomarkers. This proposal offers a comprehensive and unified approach for conducting imaging research and outcome studies utilizing imaging features.-
dc.description.statementOfResponsibilityopen-
dc.languageEnglish-
dc.publisherSpringer Nature-
dc.relation.isPartOfJOURNAL OF IMAGING INFORMATICS IN MEDICINE-
dc.rightsCC BY-NC-ND 2.0 KR-
dc.titleDevelopment of Medical Imaging Data Standardization for Imaging-Based Observational Research: OMOP Common Data Model Extension-
dc.typeArticle-
dc.contributor.collegeCollege of Medicine (의과대학)-
dc.contributor.departmentDept. of Biomedical Systems Informatics (의생명시스템정보학교실)-
dc.contributor.googleauthorWoo Yeon Park-
dc.contributor.googleauthorKyulee Jeon-
dc.contributor.googleauthorTeri Sippel Schmidt-
dc.contributor.googleauthorHaridimos Kondylakis-
dc.contributor.googleauthorTarik Alkasab-
dc.contributor.googleauthorBlake E Dewey-
dc.contributor.googleauthorSeng Chan You-
dc.contributor.googleauthorPaul Nagy-
dc.identifier.doi10.1007/s10278-024-00982-6-
dc.contributor.localIdA02478-
dc.relation.journalcodeJ04610-
dc.identifier.eissn2948-2933-
dc.identifier.pmid38315345-
dc.subject.keywordData collection [MeSH]-
dc.subject.keywordData integration-
dc.subject.keywordData standardization-
dc.subject.keywordMultimodal data analysis-
dc.subject.keywordObservational research-
dc.contributor.alternativeNameYou, Seng Chan-
dc.contributor.affiliatedAuthor유승찬-
dc.citation.volume37-
dc.citation.number2-
dc.citation.startPage899-
dc.citation.endPage908-
dc.identifier.bibliographicCitationJOURNAL OF IMAGING INFORMATICS IN MEDICINE, Vol.37(2) : 899-908, 2024-04-
Appears in Collections:
1. College of Medicine (의과대학) > Dept. of Biomedical Systems Informatics (의생명시스템정보학교실) > 1. Journal Papers

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