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Emergency Department (ED) of hospitals are greatly impacted by winter epidemics due to respiratory diseases and patient flow has long been essential to detect the underlying overcrowding. In this paper we propose to model the admission flow corresponding to clinical diagnoses encoded with ICD-10 which are more likely linked with respiratory diseases. To achieve this, clustering algorithms are applied on time evolving diagnosis in the adult ED of Saint-Etienne and benchmarked regarding a timedoi:10.1109/coase.2018.8560585 dblp:conf/case/SolerBMCPM18 fatcat:zb4o6sfc6ndfbfn653icicxfqi