Two-year death prediction models among patients with Chagas Disease using machine learning-based methods.

ABSTRACT: Chagas disease (CD) is recognized by the World Health Organization as one of the thirteen most neglected tropical diseases. More than 80% of people affected by CD will not have access to diagnosis and continued treatment, which partly supports the high morbidity and mortality rate. Machine Learning (ML) can identify patterns in data that can be used to increase our understanding of a specific problem or make predictions about the future. Thus, the aim of this study was to evaluate different models of ML to predict death in two years of patients with CD. ML models were developed using different techniques and configurations. The techniques used were: Random Forests, Adaptive Boosting, Decision Tree, Support Vector Machine, and Artificial Neural Networks. The adopted settings considered only

SUBMITTER: Ferreira AM 

PROVIDER: S-EPMC9041770 | biostudies-literature | 2022 Apr

REPOSITORIES: biostudies-literature