Implementation of Machine Learning Models for Analyzing the Correlation and Classification of Complications in Pregnancy Using Amniotic Fluid

Abstract

Amniotic fluid is an important fluid for unborn babies. This liquid surrounds the unborn baby (fetus) and helps to improve the stages of growth. The main purpose of this liquid is to proper development of lungs, bone growth, and to protect the baby from outside injury. At the time of pregnancy, the healthcare providers will give more concentration on the part of monitoring the amniotic fluid. The reduction and increasing rate of this liquid gives major problem in fetus growth as well as give the more complications in delivery. In today's strategy, nearly eight percent of the people are having problems with amniotic fluid. So, the analyzing the correlation factors and the level of amniotic fluid is a very important process to avoid problems in pregnancy. For this purpose, this chapter gives machine learning models to identify the correlation and analyze the levels of liquid present in fetus.