Abstract: This invention patent application describes mathematical methods to evaluate and validate the numbers in the conditional probability tables of a Bayesian network. Using the methods described here, the nodes of interest in the network could be evaluated for validity of the information they contain and errors could be detected by domain experts or knowledge engineers very easily. If there is a disagreement between knowledge engineers or domain experts belief of what the interaction should be and what is detected in the behavior of nodes selected for validation as shown in the reports, then, those errors could be easily located in the structure of the Bayesian network by pin pointing the table, column and row of the problematic cell. Then, the knowledge engineer or domain expert could modify the numbers to reflect the correct behavior. These methods also provide significant insight into the structure and efficiency of the structural design of the Bayesian network as well as value of information in the network.

Abstract: The present invention relates to a system and method of medical knowledge domain modeling and automated medical decision-making, such as for online, questionnaire-based medical triage. In the present invention, information such as conditions and characteristics related to a diagnosis or disposition level is modeled in a Bayesian Network. The Bayesian Network may comprise instantiable nodes, fault nodes, intermediary nodes, a utility node and a decision node. Using Bayesian inference, the conditional probability of any pair in the network may be determined in real-time. These conditional probabilities are modified upon the input of evidence, which is typically in the form of answers to a dynamic set of questions designed to identify a diagnosis or disposition level for the patient under evaluation.