SYSTÈME ET MÉTHODES POUR UNE APPROCHE BASÉE SUR L'INTELLIGENCE ARTIFICIELLE POUR L'INDICE PRÉDICTIF D'ADHÉSION AUX MÉDICAMENTS

摘要

A method for training an adherence model, the method including: extracting data for a group of individuals (510), wherein the extracted data includes demographic data (205) and clinical data (210); training a linear regression model (520) using a set of hyperparameter pairs (LI, Alpha) (515), wherein the linear regression model produces an adherence index based upon the extracted data, further including: for each hyperparameter pair (LI, Alpha) in the set of hyperparameter pairs, training the linear regression model using a training data set to produce a linear regression model for each hyperparameter pair (LI, Alpha) and calculating a performance metric R2 for the resulting model based upon a validation data set (525), wherein the training data set is a subset of the extracted data and the validation data set is a subset of the extracted data that is different from the training data set; and identifying the linear regression model with the largest performance metric R2 (530).