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Self-adaptative Early Warning Scoring System for Smart Hospital

Abstract : With the advent of the Internet of Things (IoT), various interconnected objects can be used to improve the collection and the process of vital signs with partially or fully automatized methods in smart hospital environment. The vital signs data are used to evaluate patient health status using heuristic approaches, such as the early warning scoring (EWS) approach. Several applications have been proposed based on the early warning scores approach to improve the recognition of patients at risk of deterioration. However, there is a lack of efficient tools that enable a personalized monitoring depending on the patient situations. This paper explores the publish-subscribe pattern to provide a self-adaptative early warning score system in smart hospital context. We propose an adaptative configuration of the vital sings monitoring process depending on the patient health status variation and the medical staff decisions.
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https://hal-uphf.archives-ouvertes.fr/hal-03678330
Contributor : Mylène Delrue Connect in order to contact the contributor
Submitted on : Wednesday, May 25, 2022 - 11:56:48 AM
Last modification on : Thursday, June 2, 2022 - 3:37:59 AM

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Imen Ben Ida, Moez Balti, Sondès Chaabane, Abderrazak Jemai. Self-adaptative Early Warning Scoring System for Smart Hospital. The Impact of Digital Technologies on Public Health in Developed and Developing Countries, 12157, Springer International Publishing, pp.16-27, 2020, Lecture Notes in Computer Science, 978-303051516-4. ⟨10.1007/978-3-030-51517-1_2⟩. ⟨hal-03678330⟩

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