Method, apparatus and computer program product for generating encounter vectors and client vectors using natural language processing models
AssigneeUnitedHealth Group Incorporated
InventorIrfan Bulu
Life of this patent
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Abstract
Methods, apparatuses, systems, computing devices, computing entities, and/or the like are provided. An example method may include retrieving one or more record data elements associated with a client identifier; generating one or more encounter vectors based at least in part on the one or more record data elements; generating a client vector based at least in part on the one or more encounter vectors and a first natural language processing model; generating a prediction data element based at least in part on the client vector and a machine learning model; and perform at least one data operation based at least in part on the prediction data element.
Claims20
An apparatus comprising at least one processor and at least one non-transitory memory comprising a computer program code, the at least one non-transitory memory and the computer program code configured to, with the at least one processor, cause the apparatus to:
- retrieve one or more record data elements associated with a client identifier, wherein each of the one or more record data elements is associated with an encounter identifier of one or more encounter identifiers, wherein the one or more encounter identifiers are associated with the client identifier;
- generate one or more encounter vectors based at least in part on the one or more record data elements, wherein the one or more encounter vectors are associated with the one or more encounter identifiers;
- generate a client vector based at least in part on the one or more encounter vectors, wherein the client vector is associated with the client identifier, wherein a first natural language processing model is associated with at least one of the one or more encounter vectors or the client vector;
- generate a prediction data element based at least in part on the client vector and a machine learning model, wherein the prediction data element is associated with the client identifier;
- and
- perform at least one data operation based at least in part on the prediction data element.
A computer-implemented method comprising:
- retrieving one or more record data elements associated with a client identifier, wherein each of the one or more record data elements is associated with an encounter identifier of one or more encounter identifiers, wherein the one or more encounter identifiers are associated with the client identifier;
- generating one or more encounter vectors based at least in part on the one or more record data elements, wherein the one or more encounter vectors are associated with the one or more encounter identifiers;
- generating a client vector based at least in part on the one or more encounter vectors, wherein the client vector is associated with the client identifier, wherein a first natural language processing model is associated with at least one of the one or more encounter vectors or the client vector;
- generating a prediction data element based at least in part on the client vector and a machine learning model, wherein the prediction data element is associated with the client identifier;
- and
- performing at least one data operation based at least in part on the prediction data element.
A computer program product comprising at least one non-transitory computer-readable storage medium having computer-readable program code portions stored therein, the computer-readable program code portions comprising an executable portion configured to:
- retrieve one or more record data elements associated with a client identifier, wherein each of the one or more record data elements is associated with an encounter identifier of one or more encounter identifiers, wherein the one or more encounter identifiers are associated with the client identifier;
- generate one or more encounter vectors based at least in part on the one or more record data elements, wherein the one or more encounter vectors are associated with the one or more encounter identifiers;
- generate a client vector based at least in part on the one or more encounter vectors, wherein the client vector is associated with the client identifier, wherein a first natural language processing model is associated with at least one of the one or more encounter vectors or the client vector;
- generate a prediction data element based at least in part on the client vector and a machine learning model, wherein the prediction data element is associated with the client identifier;
- and
- perform at least one data operation based at least in part on the prediction data element.
Dependencies are inferred from the claim text.