The Society of Convergence Knowledge TransactionsISSN:2287-8920(Print)융복합지식학회

Recently, the construction of learning data for the development of medical image-based disease diagnosis and prediction models has been actively conducted. However, problems with data collection and management are emerging because the level of standardization is different for each medical institution. As standardization research is progressing to solve these problems, the use of HL7 FHIR is gradually expanding in accordance with the paradigm shift in digital health. This paper introduces a novel platform designed to facilitate both individual and collaborative research across multiple institutions, leveraging the medical information standard HL7 FHIR alongside the medical imaging standard Digital Imaging and Communications in Medicine (DICOM). Our platform offers comprehensive data monitoring capabilities, ensures the anonymization and standardized storage and management of patient information according to the OMOP-CDM (Observational Medical Outcomes Partnership Common Data Model), and provides clinical information via HL7 FHIR. By utilizing HL7 FHIR resources such as Patient, Observation, DiagnosticReport, and Bundle, we enable the efficient delivery and presentation of patient information and clinical reports on the StudyList. The platform is anticipated to serve as a crucial tool for validating medical imaging data collection and artificial intelligence models in multicenter clinical research.