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Inductive creation of an annotation schema for manually indexing clinical conditions from emergency department reports

机译:归纳创建注释模式以从急诊部门报告中手动索引临床状况

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摘要

Evaluating automated indexing applications requires comparing automatically indexed terms against manual reference standard annotations. However, there are no standard guidelines for determining which words from a textual document to include in manual annotations, and the vague task can result in substantial variation among manual indexers. We applied grounded theory to emergency department reports to create an annotation schema representing syntactic and semantic variables that could be annotated when indexing clinical conditions. We describe the annotation schema, which includes variables representing medical concepts (e.g., symptom, demographics), linguistic form (e.g., noun, adjective), and modifier types (e.g., anatomic location, severity). We measured the schema’s quality and found: (1) the schema was comprehensive enough to be applied to 20 unseen reports without changes to the schema; (2) agreement between author annotators applying the schema was high, with an F measure of 93%; and (3) an error analysis showed that the authors made complementary errors when applying the schema, demonstrating that the schema incorporates both linguistic and medical expertise.
机译:评估自动索引应用程序需要将自动索引的术语与手动参考标准注释进行比较。但是,没有确定从文本文档中的哪些单词包括在手动注释中的标准准则,并且模糊的任务可能导致手动索引器之间的实质性差异。我们将扎根的理论应用于急诊科报告,以创建表示句法和语义变量的注释模式,在索引临床状况时可以对其进行注释。我们描述了注释模式,其中包括代表医学概念(例如症状,人口统计学),语言形式(例如名词,形容词)和修饰符类型(例如解剖位置,严重性)的变量。我们测量了架构的质量,发现:(1)架构足够全面,可以应用于20个看不见的报告,而无需更改架构; (2)应用模式的作者注释者之间的一致性很高,F度量为93%; (3)错误分析表明,作者在应用图式时犯了补充错误,表明该图式融合了语言学和医学专业知识。

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