Bayesian network models with decision tree analysis for management of childhood malaria in Malawi.

ABSTRACT:

Background

Malaria is a major cause of death in children under five years old in low- and middle-income countries such as Malawi. Accurate diagnosis and management of malaria can help reduce the global burden of childhood morbidity and mortality. Trained healthcare workers in rural health centers manage malaria with limited supplies of malarial diagnostic tests and drugs for treatment. A clinical decision support system that integrates predictive models to provide an accurate prediction of malaria based on clinical features could aid healthcare workers in the judicious use of testing and treatment. We developed Bayesian network (BN) models to predict the probability of malaria from clinical features and an illustrative decision tree to model the decision to use or not use a malaria

SUBMITTER: Taneja SB 

PROVIDER: S-EPMC8130361 | biostudies-literature | 2021 May

REPOSITORIES: biostudies-literature