Artificial Intelligence Recommendation System

An apparatus for facilitating recommendation prediction using machine learning, the apparatus comprising at least one processor and at least one memory including a computer program code, the at least one memory and the computer program code configured to, with the at least one processor, cause the apparatus to:

• generate embeddings data related to one or more provider entities that encodes semantic relations among latent features for provider entities, wherein the embeddings data comprises at least an embedding vector that provides a vector representation for a provider entity;
• predict a set of provider entities for a patient entity based on a provider machine learning model that is trained using the embeddings data, wherein a concatenation of user data for the patient entity and the embedding vector for the provider entity is provided to a machine learning network cell of the provider machine learning model, and wherein a machine learning network layer communicatively coupled to the machine learning network cell provides a prediction for the set of provider entities;
• rank provider entities in the set of provider entities to generate a ranked set of provider entities;
• and
• perform one or more actions to provide a recommendation for the patient entity based on the ranked set of provider entities.

A non-transitory computer storage medium comprising instructions for facilitating recommendation prediction using machine learning, the instructions being configured to cause one or more processors to at least perform operations configured to:

• generate embeddings data related to one or more provider entities that encodes semantic relations among latent features for provider entities, wherein the embeddings data comprises at least an embedding vector that provides a vector representation for a provider entity;
• predict a set of provider entities for a patient entity based on a provider machine learning model that is trained using the embeddings data, wherein a concatenation of user data for the patient entity and the embedding vector for the provider entity is provided to a machine learning network cell of the provider machine learning model, and wherein a machine learning network layer communicatively coupled to the machine learning network cell provides a prediction for the set of provider entities;
• rank provider entities in the set of provider entities to generate a ranked set of provider entities;
• and
• perform one or more actions to provide a recommendation for the patient entity based on the ranked set of provider entities.