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Large Scale Healthcare Data Integration and Analysis using the Semantic Web

机译:使用语义Web的大规模医疗数据集成和分析

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Healthcare data interoperability can only be achieved when the semantics of the content is well defined and consistently implemented across heterogeneous data sources. Achieving these objectives of interoperability requires the collaboration of experts from several domains. This paper describes tooling that integrates Semantic Web technologies with common tools to facilitate cross-domain collaborative development for the purposes of data interoperability. Our approach is divided into stages of data harmonization and representation, model transformation, and instance generation. We applied our approach on Hypergenes, an EU funded project, where we use our method to the Essential Hypertension disease model using a CDA template. Our domain expert partners include clinical providers, clinical domain researchers, healthcare information technology experts, and a variety of clinical data consumers. We show that bringing Semantic Web technologies into the healthcare interoperability toolkit increases opportunities for beneficial collaboration thus improving patient care and clinical research outcomes.
机译:当内容的语义被定义并贯穿异构数据源持续实现时,才能实现医疗保健数据互操作性。实现互操作性的这些目标需要从几个域的专家协作。本文介绍了将语义Web技术与共同工具集成的工具,以便于数据互操作性的目的促进跨域协作开发。我们的方法分为数据协调和表示,模型转换和实例生成的阶段。我们在欧盟资助的项目中应用了我们对大虾的方法,在那里我们使用我们的方法使用CDA模板来对基本高血压疾病模型的方法。我们的域名专家合作伙伴包括临床提供商,临床领域的研究人员,医疗资源技术专家以及各种临床数据消费者。我们表明将语义网络技术带入医疗保健互操作性工具包增加了有益合作的机会,从而改善了患者护理和临床研究结果。

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