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使本体与HL7 FHIR相匹配以实现其句法和语义相似性。

Matching Ontologies to HL7 FHIR Towards Their Syntactic and Semantic Similarity.

作者信息

Kiourtis Athanasios, Mavrogiorgou Argyro, Kyriazis Dimosthenis

机构信息

Department of Digital Systems, University of Piraeus, Greece.

出版信息

Stud Health Technol Inform. 2018;251:51-54.

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.

摘要

当前的医疗系统需要能够安全、高效地传输复杂而详细的医疗数据。然而,可用的医疗保健数据量正在迅速增长,远远超过了通过分析这些数据来实现个人或公共健康效益的能力。因此,需要对方法进行重大改革,以应对健康领域真正的复杂性。这可以通过构建用于表示医学术语的医学领域本体来实现,这被认为是一项艰巨的任务,需要对医学术语的结构和概念进行深入分析。本文提出了一种构建医疗保健本体的机制,同时在句法和语义相似性方面将它们与HL7 FHIR资源本体进行匹配,以便了解它们的本质并将它们转换为通用标准,以提高患者护理、研究和健康服务管理的质量。

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