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Fuzzy Ontology for Patient Emergency Department Triage

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Computational Science – ICCS 2021 (ICCS 2021)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 12744))

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Abstract

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. Our approach 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.

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Notes

  1. 1.

    https://www.w3.org/TR/owl2-overview/

  2. 2.

    https://www.health.harvard.edu/a-through-c.

  3. 3.

    https://protege.stanford.edu/

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Author information

Authors and Affiliations

  1. CRItAL Laboratory UML 9189, Villeneuve-d’Ascq, France

    Khouloud Fakhfakh, Sarah Ben Othman, Laetitia Jourdan, Slim Hammadi & Hayfa Zgaya-Biau

  2. Ecole-Central of Lille, Villeneuve-d’Ascq, France

    Khouloud Fakhfakh & Slim Hammadi

  3. Cerim, Seyssinet-Pariset, France

    Khouloud Fakhfakh, Jean Marie Renard & Hayfa Zgaya-Biau

  4. University of Lille, Lille, France

    Khouloud Fakhfakh, Sarah Ben Othman, Laetitia Jourdan, Jean Marie Renard & Hayfa Zgaya-Biau

  5. CERIM EA2694 laboratory pôle recherche aile Est 2ème étage, LUHC Lille, Lille, 1 Place de Verdun, 59045 cedex, France

    Grégoire Smith & Jean Marie Renard

Authors
  1. Khouloud Fakhfakh
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  2. Sarah Ben Othman
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  3. Laetitia Jourdan
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  4. Grégoire Smith
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  5. Jean Marie Renard
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  6. Slim Hammadi
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  7. Hayfa Zgaya-Biau
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Corresponding author

Correspondence to Khouloud Fakhfakh .

Editor information

Editors and Affiliations

  1. AGH University of Science and Technology, Krakow, Poland

    Maciej Paszynski

  2. Ludwig-Maximilians-Universität München, Munich, Germany

    Dieter Kranzlmüller

  3. University of Amsterdam, Amsterdam, The Netherlands

    Valeria V. Krzhizhanovskaya

  4. University of Tennessee at Knoxville, Knoxville, TN, USA

    Jack J. Dongarra

  5. University of Amsterdam, Amsterdam, The Netherlands

    Peter M.A. Sloot

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Fakhfakh, K. et al. (2021). Fuzzy Ontology for Patient Emergency Department Triage. In: Paszynski, M., Kranzlmüller, D., Krzhizhanovskaya, V.V., Dongarra, J.J., Sloot, P.M. (eds) Computational Science – ICCS 2021. ICCS 2021. Lecture Notes in Computer Science(), vol 12744. Springer, Cham. https://doi.org/10.1007/978-3-030-77967-2_60

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  • DOI: https://doi.org/10.1007/978-3-030-77967-2_60

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