Optimized Classification of fetal state health using GWO and WOA

Abstract

Complications in pregnancies can be due to various reasons like health issues with mother or conditions that can hamper the development of the fetus which can later affect the health of the baby. CTG performed at the time of high risk pregnancies can timely identify those associated complications. Fetuses with deficient oxygen amount are more susceptible to fetal distress which can also be fatal. This paper puts forward Grey Wolf Optimization Algorithm and Whale Optimization Algorithm for optimal feature selection from the dataset of cardiotocography. Features selected by GWO and WOA are 4 and 7 respectively. GWO and WOA efficiently select optimal reduced set of features for classification of state of the fetus under normal, suspect and pathologic with an accuracy of 98.74% and 98.11% respectively.