A new weighted rough set framework based classification for Egyptian NeoNatal Jaundice

Prediction of diseases would help physicians to make informal decision regarding the type of treatment. Jaundice is the most common condition that requires medical attention in newborn babies. Although most newborns develop some degree of jaundice, a high level bilirubin puts a newborn at risk of bilirubin encephalopathy and kernicterus, which are rare but still occur in Egypt. This paper presents a new weighted rough set framework for early intervention and prevention of neurological dysfunction and kernicterus that are catastrophic sequels of neonatal jaundice. The obtained results illustrate that the weighted rough set can provide significantly more accurate and reliable predictive accuracy than well known algorithms such as weighted SVM and decision tree considering the fact that physicians do not have any estimation about probability of jaundice appearance.

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► New weighted rough set framework for early prevention of neurological dysfunction.
► Weighted rough set can provide significantly more accurate and reliable predictive accuracy.
► The proposed framework tackles the class imbalance problem with multiple classes.