Extracting structured information from free-text medication prescriptions using dependencies

Andrew D. MacKinlay, Karin M. Verspoor
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引用次数: 8

Abstract

We explore an information extraction task where the goal is to determine the correct values for fields which are relevant to prescription drug administration such as dosage amount, frequency and route. The data set is a collection of prescriptions from a long-term health-care facility, a small subset of which we have manually annotated with values for these fields. We first examine a rule-based approach to the task, which uses a dependency parse of the prescription, achieving accuracies of 60-95% over various different fields, and 67.5% when all fields of the prescription are considered together. The outputs of such a system have potential applications in detecting irregularities in dosage delivery.
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使用依赖关系从自由文本药物处方中提取结构化信息
我们探索了一个信息提取任务,其目标是确定与处方药物给药相关的字段的正确值,如剂量、频率和路线。该数据集是来自一家长期医疗保健机构的处方集合,我们已经用这些字段的值手动注释了其中的一小部分。我们首先研究了一种基于规则的任务方法,它使用处方的依赖解析,在不同的字段上实现了60-95%的准确率,当处方的所有字段一起考虑时,实现了67.5%的准确率。这种系统的输出在检测给药中的不规则性方面具有潜在的应用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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