Interactive healthcare modeling with continuous convergence
AssigneeArchimedes, Inc.
InventorADAM GUETZ
Life of this patent
Estimating the term…
Abstract
A method comprises receiving a prediction request that comprises a target patient population definition; in response to receiving the prediction request, performing in real-time: parsing the prediction request to identify the target patient population definition; mapping the one or more target patient population characteristics to a function of one or more input variables of a particular dataset, from a plurality of datasets; computing a weighted subset of patients; based, at least in part, on the target patient population definition and the particular dataset; computing the prediction data based on the weighted subset of patients; returning the prediction data.
Claims21
-5. (canceled)
A data processing method, comprising:
- receiving a prediction request for providing estimates of health risks that may be anticipated in individuals who have one or more target patient population characteristics;
- in response to receiving the prediction request, using the prediction request, identifying the one or more target patient population characteristics;
- using a mapping function, determining a particular set of patients having one or more individual characteristics that correspond to the one or more target patient population characteristics within a tolerance range;
- computing, for the particular set of patients, one or more weights that indicate how well the one or more individual characteristics match the one or more target patient population characteristics;
- based, at least in part, on the one or more weights, selecting, from the particular set of patients, a weighted subset of patients whose computed weights exceed a threshold value;
- retrieving, from a plurality of healthcare models, a particular healthcare model that accepts data of the weighted subset of patients;
- determining prediction data by estimating, using the particular healthcare model, simulation results that a simulation based on the particular healthcare model would yield for the weighted subset of patients;
- wherein the method is performed by one or more computing devices.
A non-transitory computer-readable storage medium storing one or more sequences of instructions which, when executed by one or more processors, cause the one or more processors to perform:
- receiving a prediction request for providing estimates of health risks that may be anticipated in individuals who have one or more target patient population characteristics;
- in response to receiving the prediction request, using the prediction request, identifying the one or more target patient population characteristics;
- using a mapping function, determining a particular set of patients having one or more individual characteristics that correspond to the one or more target patient population characteristics within a tolerance range;
- computing, for the particular set of patients, one or more weights that indicate how well the one or more individual characteristics match the one or more target patient population characteristics;
- based, at least in part, on the one or more weights, selecting, from the particular set of patients, a weighted subset of patients whose computed weights exceed a threshold value;
- retrieving, from a plurality of healthcare models, a particular healthcare model that accepts data of the weighted subset of patients;
- determining prediction data by estimating, using the particular healthcare model, simulation results that a simulation based on the particular healthcare model would yield for the weighted subset of patients.
An apparatus, comprising:
- one or more processors;
- a request processor coupled to the one or more processors, and configured to perform:
- receiving a prediction request for providing estimates of health risks that may be anticipated in individuals who have one or more target patient population characteristics;
- in response to receiving the prediction request, using the prediction request, identifying the one or more target patient population characteristics;
- using a mapping function, determining a particular set of patients having one or more individual characteristics that correspond to the one or more target patient population characteristics within a tolerance range;
- computing, for the particular set of patients, one or more weights that indicate how well the one or more individual characteristics match the one or more target patient population characteristics;
- based, at least in part, on the one or more weights, selecting, from the particular set of patients, a weighted subset of patients whose computed weights exceed a threshold value;
- retrieving, from a plurality of healthcare models, a particular healthcare model that accepts data of the weighted subset of patients;
- determining prediction data by estimating, using the particular healthcare model, simulation results that a simulation based on the particular healthcare model would yield for the weighted subset of patients.
Dependencies are inferred from the claim text.