DATA DRIVEN REDUCTION OF MULTI-SCALE MODELS

摘要

A method of computing physiological measurements resulting from a multi-scale physiological system using a data-driven model includes generating a database of physiological measurements associated with a multi-scale physiological system. A computer uses dimensionality reduction techniques on the database to identify a reduced set of components explaining the multi-scale physiological system. The computer learns a data-driven model of the multi-scale physiological system from the database. Then, new input parameters are received by the computer and used to compute new physiological measurements using the data-driven model. New derived physiological indicators are computed by the computer based on the reduced set of components. Once computed, the new derived physiological indicators may be displayed along with the new physiological measurements.

主权项

1. A method of computing physiological measurements resulting from a multi-scale system using a data-driven model, the method comprising:
generating a database of physiological measurements associated with a multi-scale physiological system; using, by a computer, dimensionality reduction techniques on the database to identify a reduced set of components explaining the multi-scale physiological system; learning, by the computer, a data-driven model of the multi-scale physiological system from the database; receiving, by the computer, new input parameters; computing, by the computer, new physiological measurements from the new input parameters, using the data-driven model; computing, by the computer, new derived physiological indicators based on the reduced set of components; and displaying at least one of the new physiological measurements and the new derived physiological indicators.