Abstract:
Systems and techniques for monitoring, predicting and/or alerting for census periods in medical inpatient units are presented. A system can perform a first machine learning process to learn patterns in patient flow data related to a set of patient identities and a set of operations associated with a set of medical inpatient units. The system can also perform a second machine learning process to detect abnormalities associated with the patterns in the patient flow data. Furthermore, the system can determine patient census data associated with a prediction for a total number of patient identities in the set of medical inpatient units during a period of time based on the patterns and the abnormalities. The system can also generate an alert for a user interface in response to a determination that the patient census data satisfies a defined criterion.
Abstract:
Systems and techniques for monitoring, predicting and/or alerting for census periods in medical inpatient units are presented. A system can perform a first machine learning process to learn patterns in patient flow data related to a set of patient identities and a set of operations associated with a set of medical inpatient units. The system can also perform a second machine learning process to detect abnormalities associated with the patterns in the patient flow data. Furthermore, the system can determine patient census data associated with a prediction for a total number of patient identities in the set of medical inpatient units during a period of time based on the patterns and the abnormalities. The system can also generate an alert for a user interface in response to a determination that the patient census data satisfies a defined criterion.
Abstract:
Aspects of the present disclosure relate to a system comprising a computer-readable storage medium storing at least one program and a method for optimizing and controlling the physical and business aspects of an industrial system. In example embodiments, the method may include assessing criteria to be applied to an industrial system, and generating simulation scenarios based on the criteria. The method may further include simulating each of the simulation scenarios over a period of time to generate simulated physical aspects and simulated business aspects of the industrial system for each of the plurality of simulation scenarios. The method may further include identifying at least one of the simulation scenarios for use with the industrial system based on a comparison of the simulated physical aspects and the simulated business aspects corresponding to each simulation scenario.
Abstract:
A method for demand response management includes determining a number of available demand response events and a number of opportunities available to issue the available demand response events. A priority for each demand response event is provided and a threshold value for each demand response vent is determined. A highest priority demand response event among the available demand response events whose threshold value is lower than an observed value of a selected demand response trigger is selected and control signals to utilize the selected demand response event for a current opportunity are transmitted to customer sites.