Article ID Journal Published Year Pages File Type
496707 Applied Soft Computing 2012 7 Pages PDF
Abstract

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.

Graphical abstractFigure optionsDownload full-size imageDownload as PowerPoint slideHighlights► 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.

Related Topics
Physical Sciences and Engineering Computer Science Computer Science Applications
Authors
, ,