A Probabilistic Causal Model for Diagnosis of Liver Disorders

Abstract

Directed probabilistic graphs, such as Bayesian networks, are useful tools for coherent representation of and reasoning with uncertain knowledge. They are based on the sound foundations of probability theory and they readily combine available statistics with expert judgment. When extended with decision options and measures of desirability of outcomes (utilities), they support decision making.