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Negation Detection in Clinical Reports Written in German

机译:用德语撰写的临床报告中的否定检测

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摘要

An important subtask in clinical text mining tries to identify whether a clinical finding is expressed as present, absent or unsure in a text. This work presents a system for detecting mentions of clinical findings that are negated or just speculated. The system has been applied to two different types of German clinical texts: clinical notes and discharge summaries. Our approach is built on top of NegEx, a well known algorithm for identifying non-factive mentions of medical findings. In this work, we adjust a previous adaptation of NegEx to German and evaluate the system on our data to detect negation and speculation. The results are compared to a baseline algorithm and are analyzed for both types of clinical documents. Our system achieves an F1-Score above 0.9 on both types of reports.
机译:临床文本挖掘中的一个重要子任务试图确定临床发现是在文本中表达为当前,不存在还是不确定。这项工作提出了一种系统,用于检测被否定或仅被推测的临床发现。该系统已应用于两种不同类型的德国临床文本:临床说明和出院摘要。我们的方法建立在NegEx的基础上,NegEx是一种众所周知的算法,用于识别对医学发现的非主动性提及。在这项工作中,我们将NegEx的先前版本调整为德语,并根据我们的数据评估系统以检测否定和推测。将结果与基线算法进行比较,并对两种类型的临床文档进行分析。我们的系统在两种类型的报告上均达到F1得分高于0.9。

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