Statistical, noninvasive measurement of a patient's physiological state

An apparatus, comprising:

• a non-transitory computer readable medium having encoded thereon a set of instructions executable by one or more computers to:
• generate a model of the physiological state, wherein generating the model comprises:
• receiving data pertaining to a plurality of physiological parameters of a test subject to obtain a plurality of physiological data sets;
• directly measuring a physiological state of the test subject with a reference sensor to obtain a plurality of physiological state measurements;
• and
• correlating the received data with the physiological state of the test subject, wherein correlating the received data with the measured physiological state comprises:
• identifying a most-predictive set of signals Sk out of a set of signals s1, s2, . . . , sD for each of one or more outcomes ok, wherein the most-predictive set of signals Sk corresponds to a first data set representing a first physiological parameter, and wherein each of the one or more outcomes ok represents one of the plurality of intracranial pressure measurements;
• autonomously learning a set of probabilistic predictive models ôk=Mk(Sk), where ok is a prediction of outcome ok derived from a model Mk that uses as input values obtained from the set of signals Sk;
• and
• repeating the operation of autonomously learning incrementally from data that contains examples of values of signals s1, s2, . . . , sD and corresponding outcomes o1, o2, . . . , oK;
• receive a set of input data from one or more physiological sensors, the input data pertaining to one or more physiological parameters of a patient;
• analyze the input data against the model to generate diagnostic data concerning the patient's physiological state;
• and
• display, with a display device, at least a portion of the diagnostic data concerning the patient's physiological state.

A system, comprising:

• a computer system, comprising:
• one or more processors;
• and
• a non-transitory computer readable medium in communication with the one or more processors, the computer readable medium having encoded thereon a set of instructions executable by the computer system to:
• generate a model of the physiological state, wherein generating the model comprises:
• receiving data pertaining to a plurality of physiological parameters of a test subject to obtain a plurality of physiological data sets;
• directly measuring a physiological state of the test subject with a reference sensor to obtain a plurality of physiological state measurements;
• and
• correlating the received data with the physiological state of the test subject, wherein correlating the received data with the measured physiological state comprises:
• identifying a most-predictive set of signals Sk out of a set of signals s1, s2, . . . , sD for each of one or more outcomes Ok, wherein the most-predictive set of signals Sk corresponds to a first data set representing a first physiological parameter, and wherein each of the one or more outcomes ok represents one of the plurality of intracranial pressure measurements;
• autonomously learning a set of probabilistic predictive models ôk=Mk(Sk), where ôk is a prediction of outcome ok derived from a model Mk that uses as input values obtained from the set of signals Sk;
• and
• repeating the operation of autonomously learning incrementally from data that contains examples of values of signals s1, s2, . . . , sD and corresponding outcomes o1, o2, . . . , oK;
• receive a set of input data from one or more physiological sensors, the input data pertaining to one or more physiological parameters of a patient;
• analyze the input data against the model to generate diagnostic data concerning the patient's physiological state;
• and
• display, with a display device, at least a portion of the diagnostic data concerning the patient's physiological state.