FETAL HEALTH CLASSIFICATION USING MACHINE LEARING

Abstract: Health complications during the gestation period have evolved as a global issue. These complications sometimes result in the mortality of the fetus, which is more prevalent in developing and underdeveloped countries. The genesis of machine learning (ML) algorithms in the healthcare domain have brought remarkable progress in disease diagnosis, treatment, and prognosis. Around 800 women die every day due to pregnancy and childbirth-related issues. Maternal health and fetal health are closely associated with each other Every year approximately 3 million new born babies die because of miscarriage So there is a need for proper care including the prediction of risk levels before, during pregnancy for the safety of both mother and child. Data mining is a commonly used technique for processing enormous data. Researchers apply several data mining and machine learning techniques to analysis huge complex data, helping health care professionals to predict fetal health. In this project we used different algorithms are compared and the best model is used for predicting the fetal health.

Keywords: Machine learning, Fetal health