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Published:
Apr 17, 2019DOI:
10.4314/njt.v38i2.18Keywords:
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Main Article Content
A Bayesian Belief Network approach for predicting kernicterus
Abstract
A lot of research have been conducted using expert systems in the diagnosis of neonatal jaundice but none has been conducted on kernicterus. Kernicterus is a complication of neonatal jaundice in which bilirubin accumulates in the grey matter of the brain, causing an irreversible neurological damage. In this paper, a Bayesian belief network was designed for predicting neonatal jaundice. The BBN model has 15 nodes and had 97% and 94% accuracy in classifying neonatal jaundice and kernicterus respectively.
Keywords: Jaundice, Kernicterus, Bayesian Belief Network
