Detection Of Postpartum Hemorrhaged Using Fuzzy Deep Learning Architecture

Abstract

Maternal mortality is mainly caused because of the post-partum hemorrhage. The main goal of this research is to predict the postpartum hemorrhage based on Deep learning technique. This paper presents comparison of different deep learning approaches to achieve better performance. In this paper, Convolutional neural network concept of ZF net and VGG-16net are used for the advance observation of postpartum hemorrhage’s risk in the PPH development is predicted by Fuzzy based rules in every parameter and the performance evaluation of the system proposed is done by decreasing the rate of morbidity and mortality. Low level PPH, Average level PPH, and High level PPH are the metrics used to perform the research in this experiment. It concluded that CNN concept of VGG-16net yield outstanding performance and gave better accuracy than other techniques.