Patent ID: 8512260

Claim:
A computational method of predicting intracranial pressure, the method comprising: generating a model of intracranial pressure, 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 the test subject's intracranial pressure with a reference sensor to obtain a plurality of intracranial pressure measurements; and correlating the received data with the measured intracranial pressure of the test subject, wherein correlating the received data with the measured intracranial pressure comprises: identifying a most-predictive set of signals S k out of a set of signals s 1 , s 2 , . . . , s D for each of one or more outcomes o k , wherein the most-predictive set of signals S k corresponds to a first data set representing a first physiological parameter, and wherein each of the one or more outcomes o k represents one of the plurality of intracranial pressure measurements; autonomously learning a set of probabilistic predictive models ô k =M k (S k ), where ô k is a prediction of outcome o k derived from a model M k that uses as inputs values obtained from the set of signals S k ; and repeating the operation of autonomously learning incrementally from data that contains examples of values of signals s 1 , s 2 , . . . , s D and corresponding outcomes o 1 , o 2 , . . . , o K ; receiving, at a computer system, a set of input data from one or more physiological sensors, the input data pertaining to one or more physiological parameters of a patient; analyzing, with the computer system, the input data against the model to generate diagnostic data concerning the patient's intracranial pressure; and displaying, with a display device, at least a portion of the diagnostic data concerning the patient's intracranial pressure.