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Fuzzy Ontology for Patient Emergency Department Triage

机译:患者急诊部门的模糊本体

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Triage in emergency department (ED) is adopted procedure in several countries using different emergency severity index systems. The objective is to subdivide patients into categories of increasing acuity to allow for prioritization and reduce emergency department congestion. However, while several studies have focused on improving the triage system and managing medical resources, the classification of patients depends strongly on nurse's subjective judgment and thus is prone to human errors. So. it is crucial to set up a system able to model, classify and reason about vague, incomplete and uncertain knowledge. Thus, we propose in this paper a novel fuzzy ontology based on a new Fuzzy Emergency Severity Index (F-ESI_2.0) to improve the accuracy of current triage systems. Therefore, we model some fuzzy relevant medical subdomains that influence the patient's condition. Ourapproach is based on continuous structured and unstructured textual data over more than two years collected during patient visits to the ED of the Lille University Hospital Center (LUHC) in France. The resulting fuzzy ontology is able to model uncertain knowledge and organize the patient's passage to the ED by treating the most serious patients first. Evaluation results shows that the resulting fuzzy ontology is a complete domain ontology which can improve current triage system failures.
机译:使用不同的紧急严重性指数系统的若干国家采用急诊部门(ED)的分类。目标是将患者细分为增加敏锐性的类别,以便优先考虑并降低急诊大部分充血。然而,虽然有几项研究专注于改善分类系统并管理医疗资源,但患者的分类依赖于护士的主观判断,因此易于人类错误。所以。建立一个能够模拟,分类和含糊不清,不确定知识的系统来说至关重要。因此,我们提出了一种基于新的模糊紧急严重性指数(F-ESI_2.0)的新型模糊本体,以提高当前分类系统的准确性。因此,我们模拟了影响患者病情的一些模糊相关的医学亚域。 Ouropach基于在患者访问法国里尔大学医院中心(Luhc)的患者访问期间收集的连续结构化和非结构化文本数据。由此产生的模糊本体能够通过首先治疗最严重的患者来模拟不确定的知识并使患者的通道组织到ED。评估结果表明,由此产生的模糊本体是一种完整的域本体,可以改善电流分流系统故障。

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