Predicting congenital syphilis: Using machine learning to enhance disease management and control
Élisson da Silva Rocha,
Cleber Matos de Morais,
Igor Vitor Teixeira
et al.
Abstract:Objective: Sexually Transmitted Infections (STIs) present significant challenges to global public health, affecting physical and mental well-being and straining healthcare systems and economies. This study aims to enhance the predictive performance of models for congenital syphilis prediction by incorporating additional information obtained during gestational follow-up. Building upon the work of Teixeira et al. [1], which utilizes clinical and sociodemographic data, our model was enriched with results from ven… Show more
Set email alert for when this publication receives citations?
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.