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Semantically interoperable research medical data and meta data extraction strategy

机译:语义可互操作的研究医学数据和元数据提取策略

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Generally, the interoperability is the key feature to any widely used application or an information system. A system build on the basis of semantic data interpretation can also lead to an easy extensible and adaptable system, in the future. Otherwise, you have to deal with a lack of agreed terminologies or codes between standards e.g. DASTA vs. HL7, different coding structures and even variety of file formats or inconsistent database table schema. The most of these difficulties can be solved by the semantically interoperable system. We present our implementation strategy and meta data extraction methods for a research information system with an heterogeneous medical data. The medical data can have different origin, type, file format and even its version. We discuss the research information system that we primarily use for cerebrovascular brain diseases research.
机译:通常,互操作性是任何广泛使用的应用程序或信息系统的关键功能。在将来,基于语义数据解释构建的系统也可以导致易于扩展和适应的系统。否则,您必须处理标准之间缺乏约定的术语或代码,例如DASTA与HL7,不同的编码结构,甚至各种文件格式或不一致的数据库表架构。这些困难中的大多数可以通过语义上可互操作的系统解决。我们介绍了具有异构医学数据的研究信息系统的实施策略和元数据提取方法。医学数据可以具有不同的来源,类型,文件格式,甚至其版本。我们讨论了主要用于脑血管脑疾病研究的研究信息系统。

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