Predicting the causative pathogen among children with pneumonia using a causal Bayesian network.
BackgroundPneumonia remains a leading cause of hospitalization and death among young children worldwide, and the diagnostic challenge of differentiating bacterial from non-bacterial pneumonia is the main driver of antibiotic use for treating pneumonia in children.Causal Bayesian networks (BNs) serve as powerful tools for this problem as they provid