US 12,224,062 B2
Utilizing neural network models for recommending and adapting treatments for users
Gaston Besanson, Barcelona (ES); Frode Huse Gjendem, Barcelona (ES); Bernabé Marcos Montes, Barcelona (ES); and Joan Verdu Arnal, Taragona (ES)
Assigned to Accenture Global Solutions Limited, Dublin (IE)
Filed by Accenture Global Solutions Limited, Dublin (IE)
Filed on Feb. 1, 2021, as Appl. No. 17/164,433.
Claims priority of application No. 20383037 (EP), filed on Nov. 30, 2020.
Prior Publication US 2022/0172838 A1, Jun. 2, 2022
Int. Cl. G16H 50/20 (2018.01); A61B 5/00 (2006.01); G06N 3/045 (2023.01); G06N 3/08 (2023.01); G16H 10/60 (2018.01); G16H 20/10 (2018.01); G16H 50/30 (2018.01); G16H 50/70 (2018.01)
CPC G16H 50/20 (2018.01) [A61B 5/4836 (2013.01); A61B 5/7267 (2013.01); G06N 3/045 (2023.01); G06N 3/08 (2013.01); G16H 10/60 (2018.01); G16H 20/10 (2018.01); G16H 50/30 (2018.01); G16H 50/70 (2018.01)] 18 Claims
OG exemplary drawing
 
1. A method, comprising:
receiving, by a device, user data identifying vitals of users when receiving treatments and
dosages of the treatments;
processing, by the device, the divergence data, with a clustering model, to group the users into clusters of users, wherein the clustering model includes a hierarchical clustering model and comprises applying the hierarchical clustering model to the divergence data to group the users into the clusters of users;
training, by the device, a first neural network model, with the user data, to identify treatments for the clusters of users and to generate a trained first neural network model, wherein the training of the first neural network model includes:
receiving, by the device, a set of observations;
determining, by the device, a target variable for the set of observations; and
training, by the device, the first neural network model using the target variable;
training, by the device, a second neural network model, with the user data, to determine simulated outcomes for the treatments and to generate a trained second neural network model, wherein the training of the second neural network model includes:
obtaining, by the device, additional user data;
determining, by the device, the simulation of outcomes based on the additional user data; and
causing, by the device, the second neural network model to train, based on the simulated outcome;
generating, by the device, a treatment model based on the trained first neural network model and the trained second neural network model;
training, by the device, the treatment model with the additional user data to generate a trained treatment model;
processing, by the device, new user data identifying a new user, with the trained treatment model, to determine a recommended treatment for the new user; and
performing, by the device, one or more actions based on the recommended treatment for the new user.