Back to results
US 11,899,694 B2Granted
Techniques for temporally dynamic location-based predictive data analysis
AssigneeUnitedHealth Group Incorporated
InventorsMario M. Suarez, Elijah J. Fiore, Stephen R. Dion, Craig S. Herman
Life of this patent
Estimating the term…
Abstract
Various embodiments of the present invention provide methods, apparatus, systems, computing devices, computing entities, and/or the like for performing temporally dynamic location-based predictive data analysis. Certain embodiments of the present invention utilize systems, methods, and computer program products that perform temporally dynamic location-based predictive data analysis by utilizing at least one of prevalence-based density modeling data objects, growth-based density modeling data objects, and environment-based density modeling data objects.
Claims20
A computer-implemented method comprising:
- determining, by one or more processors and based at least in part on one or more prevalence-based density features for a primary local-temporal pair data object and one or more growth-based density features for the primary local-temporal pair data object, a predictive profile for the primary local-temporal pair data object, wherein the primary local-temporal pair data object is associated with a primary locality data object and a primary temporal unit data object;
- determining, by the one or more processors and based at least in part on the predictive profile, one or more predictive profile local-temporal pair data objects for the primary local-temporal pair data object, wherein the one or more predictive profile local-temporal pair data objects have one or more control policy temporal offsets and a same predictive profile as the primary local-temporal pair data object;
- generating, by the one or more processors, a prevalence-based density modeling data object, where the prevalence-based density modeling data object relates one or more predictive profile current periodic density measures for one or more predictive profile local-temporal pair data objects of the one or more predictive profile local-temporal pair data objects to one or more predictive profile periodic density change measures for the one or more predictive profile local-temporal pair data objects;
- generating, by the one or more processors, a growth-based density modeling data object, where the growth-based density modeling data object relates one or more predictive profile periodic density growth rate measures for one or more predictive profile local-temporal pair data objects of the one or more predictive profile local-temporal pair data objects to one or more predictive profile periodic density change measures for the one or more predictive profile local-temporal pair data objects;
- generating, by the one or more processors and based at least in part on the prevalence-based density modeling data object and the growth-based density modeling data object, a projected periodic density change measure for the primary local-temporal pair data object;
- and
- initiating, by the one or more processors, the performance of one or more prediction-based actions based at least in part on the projected periodic density change measure.
4 more elements
An apparatus comprising one or more processors and at least one memory including program code, the at least one memory and the program code configured to, with the one or more processors, cause the apparatus to at least:
- determine, based at least in part on one or more prevalence-based density features for a primary local-temporal pair data object and one or more growth-based density features for the primary local-temporal pair data object, a predictive profile for the primary local-temporal pair data object, wherein the primary local-temporal pair data object is associated with a primary locality data object and a primary temporal unit data object;
- determine, based at least in part on the predictive profile, one or more predictive profile local-temporal pair data objects for the primary local-temporal pair data object, wherein the one or more predictive profile local-temporal pair data objects have one or more control policy temporal offsets and a same predictive profile as the primary local-temporal pair data object;
- generate a prevalence-based density modeling data object, where the prevalence-based density modeling data object relates one or more predictive profile current periodic density measures for one or more predictive profile local-temporal pair data objects of the one or more predictive profile local-temporal pair data objects to one or more predictive profile periodic density change measures for the one or more predictive profile local-temporal pair data objects;
- generate a growth-based density modeling data object, where the growth-based density modeling data object relates one or more predictive profile periodic density growth rate measures for one or more predictive profile local-temporal pair data objects of the one or more predictive profile local-temporal pair data objects to one or more predictive profile periodic density change measures for the one or more predictive profile local-temporal pair data objects;
- generate, based at least in part on the prevalence-based density modeling data object and the growth-based density modeling data object, a projected periodic density change measure for the primary local-temporal pair data object;
- and
- initiate the performance of one or more prediction-based actions based at least in part on the projected periodic density change measure.
4 more elements
At at least one non-transitory computer-readable storage medium having computer-readable program code portions stored therein, the computer-readable program code portions configured to:
- determine, based at least in part on one or more prevalence-based density features for a primary local-temporal pair data object and one or more growth-based density features for the primary local-temporal pair data object, a predictive profile for the primary local-temporal pair data object, wherein the primary local-temporal pair data object is associated with a primary locality data object and a primary temporal unit data object;
- determine, based at least in part on the predictive profile, one or more predictive profile local-temporal pair data objects for the primary local-temporal pair data object, wherein the one or more predictive profile local-temporal pair data objects have one or more control policy temporal offsets and a same predictive profile as the primary local-temporal pair data object;
- generate a prevalence-based density modeling data object, where the prevalence-based density modeling data object relates one or more predictive profile current periodic density measures for one or more predictive profile local-temporal pair data objects of the one or more predictive profile local-temporal pair data objects to one or more predictive profile periodic density change measures for the one or more predictive profile local-temporal pair data objects;
- generate a growth-based density modeling data object, where the growth-based density modeling data object relates one or more predictive profile periodic density growth rate measures for one or more predictive profile local-temporal pair data objects of the one or more predictive profile local-temporal pair data objects to one or more predictive profile periodic density change measures for the one or more predictive profile local-temporal pair data objects;
- generate, based at least in part on the prevalence-based density modeling data object and the growth-based density modeling data object, a projected periodic density change measure for the primary local-temporal pair data object;
- and
- initiate the performance of one or more prediction-based actions based at least in part on the projected periodic density change measure.
4 more elements
Dependencies are inferred from the claim text.