This invention relates to the field of
machine learning scheduling technology, specifically to an intelligent
triage and
scheduling system based on
patient data streams. The
system includes a vital sign acquisition module, a deterioration distribution module, an equipment triggering module, an
access control addressing module, and a
triage and scheduling module. In this invention, multidimensional patient
monitoring data is extracted and compared with a safety baseline within a continuous observation window. Deviations are continuously accumulated and cross-aggregated to construct an objective quantitative baseline characterizing the degree of deterioration in the patient's overall condition. When the deterioration
score exceeds the takeover threshold, the
system skips the
software queuing process to locate an available physical emergency space. The underlying network switches
electronic access control and emergency equipment relays to the activation level, forcibly opening the physical emergency channel. This eliminates the
time loss caused by
critically ill patients waiting for room cleaning and equipment activation, achieving an instantaneous transition from critical vital sign data to hardware-level scheduling and control commands, ensuring that
critically ill patients receive timely and
effective treatment.