Methods and systems for grouping informed advisor pairings
AssigneeKpn Innovations, LLC.
InventorKenneth Neumann
Life of this patent
Estimating the term…
Abstract
A system for customizing informed advisor pairings, the system including a computing device. The computing device is configured to identify a user feature wherein the user feature contains a user biological extraction. The computing device is configured to generate using element training data and using a first machine-learning algorithm a first machine-learning model that outputs advisor elements. The computing device receives an informed advisor element relating to an informed advisor. The computing device determines using output advisor elements whether an informed advisor is compatible for a user.
Claims20
A system for grouping informed advisor pairings, the system comprising:
- a computing device, wherein the computing device is configured to:
- obtain a first user feature;
- determine a first prognostic user feature as a function of the first user feature, wherein determining a first prognostic user feature comprises:
- training a prognostic user feature machine learning model on a training dataset including a plurality of example user features as inputs correlated to a plurality of example prognostic user features as outputs;
- and
- generating the first prognostic user feature as a function of the first user feature using the trained prognostic user feature machine learning model;
- determine an informed advisor element as a function of the first prognostic user feature;
- group a user with an informed advisor as a function of the informed advisor element based on the first prognostic user feature;
- and
- update a user medical profile as a function of the first prognostic user feature.
A method of grouping informed advisor pairings, the method comprising:
- using at least a processor, obtaining a first user feature;
- using the at least a processor, determining a first prognostic user feature as a function of the first user feature, wherein determining a first prognostic user feature comprises:
- training a prognostic user feature machine learning model on a training dataset including a plurality of example user features as inputs correlated to a plurality of example prognostic user features as outputs;
- and
- generating the first prognostic user feature as a function of the first user feature using the trained prognostic user feature machine learning model;
- using the at least a processor, determining an informed advisor element as a function of the first prognostic user feature;
- using the at least a processor, grouping a user with an informed advisor as a function of the informed advisor element based on the first prognostic user feature;
- and
- using the at least a processor, updating a user medical profile as a function of the first prognostic user feature.
Dependencies are inferred from the claim text.