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Time-Oriented Question Answering from Clinical Narratives Using Semantic-Web Techniques

机译:使用语义网技术从临床叙事中以时间为导向的问题回答

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The ability to answer temporal-oriented questions based on clinical narratives is essential to clinical research. The temporal dimension in medical data analysis enables clinical researches on many areas, such as, disease progress, individualized treatment, and decision support. The Semantic Web provides a suitable environment to represent the temporal dimension of the clinical data and reason about them. In this paper, we introduce a Semantic-Web based framework, which provides an API for querying temporal information from clinical narratives. The framework is centered by an OWL ontology called CNTRO (Clinical Narrative Temporal Relation Ontology), and contains three major components: time normalizer, SWRL based reasoner, and OWL-DL based reasoner. We also discuss how we adopted these three components in the clinical domain, their limitations, as well as extensions that we found necessary or desirable to archive the purposes of querying time-oriented data from real-world clinical narratives.
机译:根据临床叙述回答以时间为导向的问题的能力对于临床研究至关重要。医学数据分析中的时间维度可以实现许多领域的临床研究,例如疾病进展,个性化治疗和决策支持。语义网提供了一个合适的环境来表示临床数据的时间维度及其原因。在本文中,我们介绍了一个基于语义Web的框架,该框架提供了一个用于从临床叙述中查询时间信息的API。该框架以称为CNTRO(临床叙事时间关系本体)的OWL本体为中心,并包含三个主要组件:时间标准化器,基于SWRL的推理器和基于OWL-DL的推理器。我们还将讨论如何在临床领域采用这三个组成部分,它们的局限性,以及我们发现为存档从现实世界的临床叙述中查询面向时间的数据的目的而必需或期望的扩展。

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