Extension of the HEPAR II Model to Multiple-Disorder Diagnosis

The Hepar II system is based on a Bayesian network model of a subset of the domain of hepatology in which the structure of the network is elicited from an expert diagnostician and the parameters are learned from a database of medical cases. The model follows the assumption made in the database that each patient case is diagnosed with a single disorder, i.e., disorders are mutually exclusive. In this paper, we describe an extension of the Hepar II system to multipledisorder diagnosis. We show that our network transforms readily to a network that can perform multiple-disorder diagnosis with some bene ts to the quality of numerical parameters learned from the database. We demonstrate empirically that the diagnostic performance in terms of single-disorder diagnosis improves under this transformation. The new model is more realistic and we expect that it will be of higher value in clinical practice.

• Type: Conference
• Year: 2000
• Where: IIS
• Authors: Agnieszka Onisko, Marek Druzdezel, Hanna Wasyluk
• Keywords: Bayesian Network Model, Expert Diagnostician, Hepar II, IIS 2000, IIS 2001