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Augmenting medical case base reasoning systems with clinical knowledge derived from heterogeneous electronic patient records

机译:利用来自异构电子病历的临床知识增强医疗案例推理系统

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The development of medical case-based reasoning (CBR) systems necessitates the active involvement of medical experts. The work featured in this paper aims to minimize the involvement of medical experts in enhancing the knowledge content of medical CBR systems by using causal information contained in a generic electronic patient record (EPR) as an alternate source of CBR-compliant cases. We present an automated case acquisition and transcription information structure that features: (a) an agent to proactively procure XML-based EPRs from Internet-accessible EPR repositories; and (b) a case generation methodology to automatically transform generic EPRs into specialized CBR-compliant clinical cases (CCs). EPR-CC transformation is achieved by establishing a multi-level equivalence between the EPR and CC constructs .e. structural equivalence via meta-data constructs, terminological equivalence via a meta-thesaurus and conceptual equivalence via domain-specific ontologies. The transformed CCs are intended to be seamlessly incorporated within CBR-based medical diagnostic systems.
机译:基于医疗案例推理(CBR)系统的开发需要医学专家的积极参与。本文中的工作旨在通过使用通用电子病历(EPR)中包含的因果信息作为符合CBR的病例的替代来源,来最大程度地减少医学专家对增强CBR系统的知识内容的参与。我们提供了一种自动化的案例获取和转录信息结构,其特点是:(a)从互联网可访问的EPR存储库中主动获取基于XML的EPR的代理; (b)一种案例生成方法,可将通用EPR自动转换为符合CBR的专业临床案例(CC)。 EPR-CC转换是通过在EPR和CC构造之间建立多级等效来实现的。e。通过元数据结构进行结构对等,通过元同义词库进行术语对等以及通过特定领域本体进行概念对等。转换后的CC旨在无缝集成到基于CBR的医学诊断系统中。

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