Fetal Health Prediction

Fetal health serves as a crucial indicator of the well- being of the unborn child, with regular monitoring within the pregnant woman's uterus being essential throughout pregnancy. Complications during pregnancy can significantly impact fetal development, potentially leading to severe issues or even fetal loss. Safeguarding the pregnancy period involves identifying and predicting risk factors well in advance to promote optimal fetal growth. Utilizing data mining algorithms to develop predictive classifier models based on pre-classified patterns is a common approach in predicting fetal health status. This study focuses on leveraging the dataset, comprising 2126 instances with 22 attributes derived from the construct a model for predicting fetal health. The primary objective is to select efficient data mining techniques that yield accurate predictive models to enhance the management of fetal health during pregnancy.