Application of Bayesian belief networks to diagnosis of liver disorders

Authors:

Agnieszka Onisko
Bialystok University of Technology
Institute of Computer Science
Bialystok, 15-351, Poland
e-mail: aonisko@ii.pb.bialystok.pl
FAX: (085) 422-393

Marek J. Druzdzel
Decision Systems Laboratory
School of Information Sciences
and Intelligent Systems Program
University of Pittsburgh
e-mail: marek@sis.pitt.edu

Hanna Wasyluk
The Medical Center of Postgraduate Education
Warsaw, Marymoncka 99, Poland
e-mail: hwasyluk@cmkp.edu.pl
FAX: (022) 340-470

Abstract:

Probabilistic graphs, such as Bayesian belief networks, are useful tools for coherent representation of uncertain knowledge. They are based on the sound foundations of probability theory and they readily combine available frequency data with expert assessments. When extended with measures of desirability of outcomes, utilities, they support decision making. This paper describes our work in progress on application of Bayesian belief networks to diagnosis of liver disorders. We discuss our initial model and how it was constructed, including both its structure and parametrization.

Keywords: Bayesian belief networks, diagnosis.