A Boosting Approach for Maternal Hypertensive Disorder Detection

Pregnancy is the delicate stage in every woman's life cycle. The changes in the health during this period may lead to risk in pregnancy. That is a high risk pregnancy is one that endangers the women's or baby's health or life. Hypertensive disorders are the most common cause of these pregnancy related complications. In the present era, it's a major challenge in health care because their results in increasing maternal and fetal death. There exist various techniques widely used in data mining for the early identification of health diseases. Better treatment can be provided in the early stage by the early identification of hypertensive disorders. The main intent of this paper is to pinpoint the present complications of a pregnant woman by applying a boosted random forest approach for predicting hypertensive disorders. This classification method helps to predict the risks, diagnose and thereby can decrease maternal and fetal mortality, which remains as a large problem in much of the developing nation.