Hybrid system based on bijective soft and neural network for Egyptian neonatal jaundice diagnosis. (2016)

• Record Type: Journal Article
• Authors: Azar, Ahmad Taher; Inbarani, H. Hannah; Kumar, S. Udhaya; Own, Hala Shawky
• Is Part Of: International journal of intelligent engineering informatics. Volume 4: Number 1 (2016)
• Page Start: 71
• Page End: 90
• Publication Date: 2016
• Subjects: bijective soft sets -- neonatal jaundice -- bijective soft set neural networks -- BISONN -- feature selection -- disease classification -- Egypt -- newborns -- hyperbilirubinemia -- acute bilirubin encephalopathy -- ABE -- kernicterus -- jaundice diagnosis -- Egypt -- newborn infants -- newborn babies; Artificial intelligence -- Engineering applications -- Periodicals; Engineering -- Computer programs -- Periodicals; Knowledge management -- Periodicals; 620.0028563
• Languages: English
• ISSNs: 1758-8715

Abstract

Neonatal jaundice or hyperbilirubinemia and its evolution to acute bilirubin encephalopathy (ABE) and kernicterus are an important, yet avoidable, origin of newborn deaths, re-hospitalisations and disabilities generally. In this study, a new supervised hybrid bijective soft set neural network-based classification method is introduced for prediction of Egyptian neonatal jaundice dataset. Early prediction and classification of diseases would provide support to doctors for making decision of patient concerning the type of treatment. The hybrid bijective soft set neural network (BISONN) approach integrates both bijective soft set and back propagation neural network for the diagnosis of diseases. The experimental results are acquired by examining the proposed method on neonatal jaundice. The acquired results demonstrate that the hybrid bijective soft set neural network method can deliver expressively more accurate and consistent predictive accuracy than well-known algorithms such as bijective soft set classifier, back propagation network, multi-layered perceptron, decision table and naïve Bayes classification algorithms.