Ontology for Overcrowding Management in ...
Type de document :
Article dans une revue scientifique: Article original
DOI :
PMID :
URL permanente :
Titre :
Ontology for Overcrowding Management in Emergency Department.
Auteur(s) :
Fakhfakh Maala, Khouloud [Auteur]
Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 [CRIStAL]
Université Lille Nord (France)
Ben Othman, Sarah [Auteur]
Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 [CRIStAL]
Jourdan, Laetitia [Auteur]
Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 [CRIStAL]
Smith, Grégoire [Auteur]
Université Lille Nord (France)
Renard, Jean-Marie [Auteur]
METRICS : Evaluation des technologies de santé et des pratiques médicales - ULR 2694
Université Lille Nord (France)
Hammadi, Slim [Auteur]
Centre de Recherche en Informatique, Signal et Automatique de Lille (CRIStAL) - UMR 9189
Zgaya Biau, Hayfa [Auteur]
Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 [CRIStAL]
Université Lille Nord (France)
Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 [CRIStAL]
Université Lille Nord (France)
Ben Othman, Sarah [Auteur]
Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 [CRIStAL]
Jourdan, Laetitia [Auteur]
Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 [CRIStAL]
Smith, Grégoire [Auteur]
Université Lille Nord (France)
Renard, Jean-Marie [Auteur]
METRICS : Evaluation des technologies de santé et des pratiques médicales - ULR 2694
Université Lille Nord (France)
Hammadi, Slim [Auteur]
Centre de Recherche en Informatique, Signal et Automatique de Lille (CRIStAL) - UMR 9189
Zgaya Biau, Hayfa [Auteur]
Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 [CRIStAL]
Université Lille Nord (France)
Titre de la revue :
Studies in Health Technology and Informatics
Nom court de la revue :
Stud Health Technol Inform
Numéro :
290
Pagination :
947-951
Date de publication :
2022-06-14
ISSN :
1879-8365
Discipline(s) HAL :
Sciences du Vivant [q-bio]
Résumé en anglais : [en]
Emergency department (ED) overcrowding is an ongoing problem worldwide. Scoring systems are available for the detection of this problem. This study aims to combine a model that allows the detection and management of ...
Lire la suite >Emergency department (ED) overcrowding is an ongoing problem worldwide. Scoring systems are available for the detection of this problem. This study aims to combine a model that allows the detection and management of overcrowding. Therefore, it is crucial to implement a system that can reason model, rank ED resources and ED performance indicators based on environmental factors. Thus, we propose in this paper a new domain ontology (EDOMO) based on a new overcrowding estimation score (OES) to detect critical situations, specify the level of overcrowding and propose solutions to deal with these situations. Our approach is based on a real database created during more than four years from the Lille University Hospital Center (LUHC) in France. The resulting ontology is capable of modeling complete domain knowledge to enable semantic reasoning based on SWRL rules. The evaluation results show that the EDOMO is complete that can enhance the functioning of the ED.Lire moins >
Lire la suite >Emergency department (ED) overcrowding is an ongoing problem worldwide. Scoring systems are available for the detection of this problem. This study aims to combine a model that allows the detection and management of overcrowding. Therefore, it is crucial to implement a system that can reason model, rank ED resources and ED performance indicators based on environmental factors. Thus, we propose in this paper a new domain ontology (EDOMO) based on a new overcrowding estimation score (OES) to detect critical situations, specify the level of overcrowding and propose solutions to deal with these situations. Our approach is based on a real database created during more than four years from the Lille University Hospital Center (LUHC) in France. The resulting ontology is capable of modeling complete domain knowledge to enable semantic reasoning based on SWRL rules. The evaluation results show that the EDOMO is complete that can enhance the functioning of the ED.Lire moins >
Langue :
Anglais
Audience :
Internationale
Vulgarisation :
Non
Établissement(s) :
Université de Lille
CHU Lille
CHU Lille
Date de dépôt :
2023-11-15T03:56:59Z
2024-01-15T15:05:48Z
2024-01-15T15:05:48Z
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- SHTI-290-SHTI220220.pdf
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