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DEDUCE: A pattern matching method for automatic de-identification of Dutch medical text

机译:减少:一种模式匹配方法,用于自动取消识别荷兰医学文本

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摘要

In order to use medical text for research purposes, it is necessary to de-identify the text for legal and privacy reasons. We report on a pattern matching method to automatically de-identify medical text written in Dutch, which requires a low amount of effort to be hand tailored. First, a selection of Protected Health Information (PHI) categories is determined in cooperation with medical staff. Then, we devise a method for de-identifying all information in one of these PHI categories, that relies on lookup tables, decision rules and fuzzy string matching. Our de-identification method DEDUCE is validated on a test corpus of 200 nursing notes and 200 treatment plans obtained from the University Medical Center Utrecht (UMCU) in the Netherlands, achieving a total micro-averaged precision of 0.814, a recall of 0.916 and a F-1-score of 0.862. For person names, a recall of 0.964 was achieved, while no names of patients were missed.
机译:为了将医学文本用于研究目的,出于法律和隐私原因,有必要取消对文本的标识。我们报告了一种模式匹配方法,该方法可以自动识别以荷兰语编写的医学文本,这需要手工进行少量工作。首先,与医务人员合作确定受保护的健康信息(PHI)类别的选择。然后,我们设计了一种方法,该方法依赖于查找表,决策规则和模糊字符串匹配来对这些PHI类别之一中的所有信息进行去识别。我们从荷兰乌得勒支大学医学中心(UMCU)获得的200份护理笔记和200份治疗计划的测试语料库对我们的去识别方法DEDUCE进行了验证,总平均精确度达到0.814,召回率为0.916, F-1-得分为0.862。对于人名,召回率为0.964,而没有遗漏患者姓名。

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