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Towards practical temporal relation extraction from clinical notes: An analysis of direct temporal relations

机译:从临床笔记中寻求实用的时态关系提取:直接时态关系分析

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Following the conventions developed in general domain, most of the current work on clinical temporal relation identification aims to identify a comprehensive set of temporal relations from source documents. This includes both explicit relations that is described in the documents and implicit relations that are identifiable only through inference. Although such an approach may provide a complete view of temporal information provided in a document, some temporal relations may not be practically essential, depending on the clinical application at hand. In addition, the performances of current systems that identify both explicit and implicit relations are still low and how to enhance the performances to be enough for practical use is not clear yet. In this paper, we propose focus on a subset of temporal relations, in order to provide insights into how to develop practically useful temporal information extraction methods for clinical text. We focus on “direct” temporal relations, which are intra-sentential temporal relations between a time expression and an event mention with limited syntactic distance. A corpus of 120 discharge summaries is constructed, leveraging an existing corpus, the 2012 i2b2 corpus. We show that the direct temporal relations constitute a major category of temporal relations. In addition, we show that the performance of the state-of-the art temporal relation extraction system, which is developed for both implicit and explicit relations, on direct temporal relations is still low. This indicates the need for development of methods tailored to direct temporal relations.
机译:遵循在一般领域制定的约定,当前有关临床时态关系识别的大多数工作旨在从源文档中识别出一套全面的时态关系。这既包括文档中描述的显式关系,也包括只能通过推理来识别的隐式关系。尽管这种方法可以提供文档中提供的时间信息的完整视图,但是某些时间关系实际上并不是必需的,具体取决于当前的临床应用。另外,识别显式和隐式关系的当前系统的性能仍然很低,并且如何增强性能以使其足以实际使用尚不清楚。在本文中,我们建议关注时间关系的子集,以提供有关如何为临床文本开发实用的时间信息提取方法的见解。我们关注“直接”时间关系,这是时间表达和事件提及之间在句法距离有限的情况下的句内时间关系。利用现有的语料库2012 i2b2语料库,构建了一个包含120个放电摘要的语料库。我们表明,直接时间关系构成时间关系的主要类别。另外,我们表明,针对直接时间关系开发的针对隐式和显式关系开发的最新时间关系提取系统的性能仍然很低。这表明需要开发适合于直接时间关系的方法。

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