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Following Ang et al [36] and Carmeli et al [37], we incorporated queuing theory–based results as features in machine learning methods. We started by estimating the workload in each procedure of ED care. For example, we calculated the number of people queued for a computed tomography (CT) scan when a specific patient entered this queue, and the service rate of the CT scan (ie, the number of patients who undergo a CT scan per hour).
JMIR Form Res 2020;4(2):e16410
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