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基于标准的程序表型分析:i2b2上的 Arden 语法

Standards-Based Procedural Phenotyping: The Arden Syntax on i2b2.

作者信息

Mate Sebastian, Castellanos Ixchel, Ganslandt Thomas, Prokosch Hans-Ulrich, Kraus Stefan

机构信息

Medical Informatics, Univ. of Erlangen-Nürnberg, Erlangen, Germany.

Department of Anesthesiology, University Hospital Erlangen, Erlangen, Germany.

出版信息

Stud Health Technol Inform. 2017;243:37-41.

Abstract

Phenotyping, or the identification of patient cohorts, is a recurring challenge in medical informatics. While there are open source tools such as i2b2 that address this problem by providing user-friendly querying interfaces, these platforms lack semantic expressiveness to model complex phenotyping algorithms. The Arden Syntax provides procedural programming language construct, designed specifically for medical decision support and knowledge transfer. In this work, we investigate how language constructs of the Arden Syntax can be used for generic phenotyping. We implemented a prototypical tool to integrate i2b2 with an open source Arden execution environment. To demonstrate the applicability of our approach, we used the tool together with an Arden-based phenotyping algorithm to derive statistics about ICU-acquired hypernatremia. Finally, we discuss how the combination of i2b2's user-friendly cohort pre-selection and Arden's procedural expressiveness could benefit phenotyping.

摘要

表型分析,即患者队列的识别,是医学信息学中一个反复出现的挑战。虽然有诸如i2b2这样的开源工具,通过提供用户友好的查询接口来解决这个问题,但这些平台缺乏语义表达能力来对复杂的表型分析算法进行建模。Arden语法提供了过程编程语言结构,专门为医学决策支持和知识转移而设计。在这项工作中,我们研究了Arden语法的语言结构如何用于通用表型分析。我们实现了一个原型工具,将i2b2与开源的Arden执行环境集成在一起。为了证明我们方法的适用性,我们将该工具与基于Arden的表型分析算法一起使用,以得出关于重症监护病房获得性高钠血症的统计数据。最后,我们讨论了i2b2用户友好的队列预选择与Arden的过程表达能力相结合如何能使表型分析受益。

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