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Matching Ontologies to HL7 FHIR Towards Their Syntactic and Semantic Similarity
Athanasios Kiourtis1, Argyro Mavrogiorgou1, Dimosthenis Kyriazis1
1Department of Digital Systems, University of Piraeus, Greece.
Abstract:
Current medical systems need to be able to communicate complex and detailed medical data securely and efficiently. However, the quantity of available healthcare data is rising rapidly, far exceeding the capacity to deliver personal or public health benefits from analyzing this data. Thus, a substantial overhaul of methodology is required to address the real complexity of health. This can be achieved by constructing medical domain ontologies for representing medical terminologies, considered to be a difficult task, requiring a profound analysis of the structure and the concepts of medical terminologies. In this paper, a mechanism is presented for constructing healthcare ontologies, while matching them to HL7 FHIR Resources ontologies both in terms of syntactic and semantic similarity, in order to understand their nature and translate them into a common standard to improve the quality of patient care, research, and health service management.
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