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Journal Articles IOS press EBooks Year : 2022

Analysis of Saturation in the Emergency Department: A Data-Driven Queuing Model Using Machine Learning

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Abstract

Emergency department is a key component of the health system where the management of crowding situations is crucial to the well-being of patients. This study proposes a new machine learning methodology and a queuing network model to measure and optimize crowding through a congestion indicator, which indicates a real-time level saturation.

Dates and versions

hal-03688662 , version 1 (05-06-2022)

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Cite

Adrien Wartelle, Farah Mourad-Chehade, Farouk Yalaoui, David Laplanche, Stéphane Sanchez. Analysis of Saturation in the Emergency Department: A Data-Driven Queuing Model Using Machine Learning. IOS press EBooks, 2022, Studies in Health Technology and Informatics, ⟨10.3233/SHTI220402⟩. ⟨hal-03688662⟩
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