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分析用于后基因组临床试验语义互操作性的SNOMED CT和HL7术语绑定。

Analyzing SNOMED CT and HL7 terminology binding for semantic interoperability on post-genomic clinical trials.

作者信息

Aso Santiago, Perez-Rey David, Alonso-Calvo Raul, Rico-Diez Antonio, Bucur Anca, Claerhout Brecht, Maojo Victor

机构信息

Biomedical Informatics Group, DIA & DLSIIS, Facultad de Informática, Universidad Politécnica de Madrid, Campus de Montegancedo S/N, 28660 Boadilla del Monte, Madrid, Spain.

出版信息

Stud Health Technol Inform. 2013;192:980.

Abstract

Current post-genomic clinical trials in cancer involve the collaboration of several institutions. Multi-centric retrospective analysis requires advanced methods to ensure semantic interoperability. In this scenario, the objective of the EU funded INTEGRATE project, is to provide an infrastructure to share knowledge and data in post-genomic breast cancer clinical trials. This paper presents the process carried out in this project, to bind domain terminologies in the area, such as SNOMED CT, with the HL7 v3 Reference Information Model (RIM). The proposed terminology binding follow the HL7 recommendations, but should also consider important issues such as overlapping concepts and domain terminology coverage. Although there are limitations due to the large heterogeneity of the data in the area, the proposed process has been successfully applied within the context of the INTEGRATE project. An improvement in semantic interoperability of patient data from modern breast cancer clinical trials, aims to enhance the clinical practice in oncology.

摘要

当前癌症领域的后基因组临床试验涉及多个机构的合作。多中心回顾性分析需要先进的方法来确保语义互操作性。在这种情况下,欧盟资助的INTEGRATE项目的目标是提供一个基础设施,以便在后基因组乳腺癌临床试验中共享知识和数据。本文介绍了该项目中所开展的将该领域的领域术语(如SNOMED CT)与HL7 v3参考信息模型(RIM)相结合的过程。所提出的术语绑定遵循HL7的建议,但也应考虑诸如概念重叠和领域术语覆盖范围等重要问题。尽管由于该领域数据的巨大异质性存在局限性,但所提出的过程已在INTEGRATE项目的背景下成功应用。现代乳腺癌临床试验中患者数据语义互操作性的改善旨在提升肿瘤学的临床实践。

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