Introduction to Bayesian Networks
Introduction to Bayesian Networks
Probabilities for a probabilistic network: a case study in oesophageal cancer
Artificial Intelligence in Medicine
Generalised reliability characteristics for probabilistic networks
Artificial Intelligence in Medicine
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In most medical disciplines, the results from diagnostic tests are not unequivocal. To capture the uncertainties in test results, the notions of sensitivity and specificity of diagnostic tests have been introduced. Although the importance of taking these test characteristics into account in medical reasoning is stressed throughout the literature, they are often not modelled explicitly in real-life probabilistic networks. In this paper, we study the effects that disregarding the characteristics of diagnostic tests can have on the performance of a probabilistic network. We feel that the effects that we observed in a real-life network for the staging of oesophageal cancer, are likely to be found in networks for other applications in medicine as well.