부산대학교 도서관

The life of a woman also necessitates attention and treatment. Generally, a woman’s well-being receives consideration only during pregnancy due to changes in a few physiological parameters, which can lead to severe conditions or death in some instances. The best thing we can do for pregnant women is to support them through their unfavorable pregnancy outcomes. Many strategies in machine learning (ML) and artificial intelligence (AI) have described their different data sets using various approaches. In addition, the research explains how this technology is applied to the interactive example. From that example, we predicted a survey with additional data in Andhra Pradesh. More analysis has been made on pregnancy outcomes by considering different ages to solve the risk factors of pregnant women either during pregnancy or after pregnancy. Many studies have been completed, and the aim of this manuscript is to extant the results of those studies in a graphical model. The principal objective of this research work is to represent the different risks associated with pregnancy. The field of ML is an offshoot of computer science engineering that aims to give machines the ability to complete a particular activity without needing to be programmed. We could provide a quick look at the capabilities of machine learning techniques to enhance output function assessment by optimizing the problem in pregnant women and to help strengthen prenatal diagnoses by different Machine learning algorithms. [ABSTRACT FROM AUTHOR]