Predictive Analysis of Postpartum Haemorrhage Using Deep Learning Technique

Abstract

Postpartum haemorrhage is the prime source of parental fatality. Postpartum haemorrhage occurs extra blood loss after delivery. If the blood loss occurs more than 500ml, it may create a problem in blood pressure where the women has to go through a lot of pain. Presently, the complete cure are still under research and there is no result which helps to dwindle the endanger of postpartum haemorrhage. Intent process is so supportive in classifying the danger circumstances and current automation is used. The methodology used here is Deep Learning technique which will be easier to conclude the postpartum haemorrhage in the previous phase. There is an certain stage of postpartum haemorrhage where it can control the blood loss and save the women by permitting higher level treatments. Haemorrhage is one of the major factor responsible for maternal death. Haemorrhage may occur before, during or after delivery of placenta. Based on the amount of blood flow, postpartum haemorrhage will be classified in to two types such as primary and secondary pph. To manage all these problems, methods are handled based on respective situation.