A prototype for the recommendation of treatment-resistant depression treatments (INFORMS)

Abstract

This work consists of a prototype for the personalized recommendations of treatment-resistant depression treatments using recommender systems. After characterizing our dataset, we explore in this work the performance of a factorization machine with two different treatment definitions as well as different variables describing the patients and treatments.