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Cyber-Physical Orchestration of Emergency Department Services Through a Bidirectional Digital Twin and a Deep Reinforcement Learning Agent: Architectural Design, In SilicoValidation, and Critical Analysis of Performance Under Demand Stress

2026-07-28

Abstract excerpt

<title>Abstract</title> <p> <bold>Background.</bold> Hospital emergency departments operate as non-stationary, multiclass queueing systems with shared resources, in which stochastic demand and short-run fixed capacity generate bottlenecks that erode clinical safety as crowding intensifies. Predictive <italic>Machine Learning</italic> models have proven superior to manual triage scales for anticipating clinica...

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Literature Corpus work: d8319173-25e2-55f8-915b-5bd7955aeb3d
DOI: 10.21203/rs.3.rs-10475510/v1

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Cyber-Physical Orchestration of Emergency Department Services Through a Bidirectional Digital Twin and a Deep Reinforcement Learning Agent: Architectural Design, In SilicoValidation, and Critical Analysis of Performance Under Demand StressDOI 10.21203/rs.3.rs-10475510/v1Read

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