Utilizing neural network models for recommending and adapting treatments for users

Abstract

A device may receive user data identifying vitals of users when receiving treatments and dosages of the treatments, and may process the user data, with a divergence model, to determine divergence data identifying divergences between the users. The device may process the divergence data, with a clustering model, to group the users into clusters of users, and may train a first neural network model, with the user data, to generate a trained first neural network model. The device may train a second neural network model, with the user data, to generate a trained second neural network model, and may generate a treatment model based on the trained first and second neural network models. The device may process new user data identifying a new user, with the treatment model, to determine a recommended treatment for the new user, and may perform one or more actions based on the recommended treatment.