Accurate temporal event predictive modeling
AssigneeInternational Business Machines Corporation
InventorsCharu C. Aggarwal, Lingtao Cao, Tan Hung M. Ng, Saket Sathe, Deepak S. Turaga
Life of this patent
Estimating the term…
Abstract
Embodiments for accurate temporal event predictive modeling by a processor. An average reverse event delay may be determined from one or more event delays in a time-series window. A time-series event may be predicted by applying the average reverse event delay in conjunction with one or more weighted factors in a predictive model.
Claims20
A method for accurate temporal event predictive modeling by a processor, comprising:
- identifying a plurality of time-series windows;
- determining, for each time-series window, a reverse event delay, wherein the reverse event delay is an amount of time between the end of the time-series window and an occurrence of a corresponding hypoglycemic event;
- determining, for each time-series window, an event delay, wherein the event delay is an amount of time between the start of the time-series window and the occurrence of the corresponding hypoglycemic event;
- computing an average reverse event delay and an average event delay for the plurality of time-series windows;
- training a predictive model for predicting hypoglycemic events using at least the average reverse event delay and the average event delay as weighted factors in the predictive model.
A system comprising:
- a processor configured to perform a method comprising:
- identifying a plurality of time-series windows;
- determining, for each time-series window, a reverse event delay, wherein the reverse event delay is an amount of time between the end of the time-series window and an occurrence of a corresponding hypoglycemic event;
- determining, for each time-series window, an event delay, wherein the event delay is an amount of time between the start of the time-series window and the occurrence of the corresponding hypoglycemic event;
- computing an average reverse event delay and an average event delay for the plurality of time-series windows;
- training a predictive model for predicting hypoglycemic events using at least the average reverse event delay and the average event delay as weighted factors in the predictive model.
A computer program product, the computer program product comprising a computer readable storage medium having program instructions embodied therewith, the program instructions executable by a processor to cause the processor to perform a method comprising:
- identifying a plurality of time-series windows;
- determining, for each time-series window, a reverse event delay, wherein the reverse event delay is an amount of time between the end of the time-series window and an occurrence of a corresponding hypoglycemic event;
- determining, for each time-series window, an event delay, wherein the event delay is an amount of time between the start of the time-series window and the occurrence of the corresponding hypoglycemic event;
- computing an average reverse event delay and an average event delay for the plurality of time-series windows;
- training a predictive model for predicting hypoglycemic events using at least the average reverse event delay and the average event delay as weighted factors in the predictive model.
Dependencies are inferred from the claim text.