Early warning system modeling for patient bispectral index prognosis in anesthesia and the operating room

Bispectral index (BIS) is a popular technology widely used in hospitals to monitor depth of patients' anesthesia during surgeries. Maintaining a proper, steady state of the patient's BIS level is critical for patient safety. In this paper an autoregressive moving average model is implemented on patient BIS data for the prognosis of the depth of anesthesia. This prognosis will enable anesthesiologists to make adjustments to the anesthetics prior to a shift in the BIS for the purpose of maintaining steady state BIS. This proposed method will alleviate the current demand for anesthesiologists to make their own predictions during surgery based on past experiences.

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