Systems and Methods For Preparation And Retrieval Of User-Level Treatment Recommendations From A Machine Learning Model

A computing device, comprising:

• a processor;
• and
• a non-transitory computer-readable medium having stored thereon instructions that, when executed by the processor, cause the processor to perform operations including:
• receiving a request for a treatment recommendation, wherein the request includes a user identifier (ID), and wherein a treatment is a notification, alert, or message to be provided by a network device,
• retrieving (i) a set of user data from an aggregated user data table according to the user ID, and (ii) treatment data comprised of data related to a set of predefined treatments from a treatment datastore,
• deploying a machine learning model configured to take the set of user data, a set of candidate treatments, and a configured objective as input and provide a scoring for each of the set of candidate treatments, wherein the set of candidate treatments is selected from the set of predefined treatments according to application of a set of eligibility rules, and wherein the machine learning model is trained and configured to score each of the set of candidate treatments according to the configured objective,
• generating a ranked list of the set of candidate treatments based on the scoring provided by the machine learning model, and
• providing the ranked list of the set of candidate treatments and the set of candidate treatments to the network device.

A non-transitory computer-readable medium having stored thereon instructions that, when executed by one or more processors, cause the one or more processor to perform operations including:

• receiving a request for a treatment recommendation, wherein the request includes a user identifier (ID), and wherein a treatment is a notification, alert, or message to be provided by a network device;
• retrieving (i) a set of user data from an aggregated user data table according to the user ID, and (ii) treatment data comprised of data related to a set of predefined treatments from a treatment datastore;
• deploying a machine learning model configured to take the set of user data, a set of candidate treatments, and a configured objective as input and provide a scoring for each of the set of candidate treatments, wherein the set of candidate treatments is selected from the set of predefined treatments according to application of a set of eligibility rules, and wherein the machine learning model is trained and configured to score each of the set of candidate treatments according to the configured objective;
• generating a ranked list of the set of candidate treatments based on the scoring provided by the machine learning model;
• and
• providing the ranked list of the set of candidate treatments and the set of candidate treatments to the network device.