DETERMINING THE CONDITIONAL PROBABILITIES IN BAYESIAN NETWORKS

Year 2004, Volume: 33 , 69 - 76, 01.01.2004

Hülya Olmuş S. Oral Erbaş

Abstract

Bayesian networks are used to illustrate how the probability of hav-

ing a disease can be updated given the results from clinical tests. The

problem of diagnosis, that is of determining whether a certain disease

is present, $D$, or absent, $D'$, based on the result of a medical test, is

discussed. Using statistical methods for medical diagnosis, informa-

tion about the disease and symptoms are collected and the databases

are used to diagnose new patients. How can we evaluate the diagnos-

tic probability represented by Pr($D$\ evidence), where evidence is the

result of a clinical test or tests on a new patient? The object of this ar-

ticle is to answer this question. Using the HUGIN software, diagnostic

probabilities are analyzed using the Bayesian approach.

Keywords

Bayesian networks, Medical diagnosis, Conditional probability

References

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