Enhancing Maternal Health: A Soft Computing Approach to Pregnancy Risk Management

Abstract

Enhancing maternal health is a crucial pursuit in modern healthcare, especially when it comes to managing the risks associated with pregnancy. This chapter presents an innovative strategy that utilizes soft computing techniques to enhance the evaluation and handling of pregnancy-related risks. Soft computing, known for its ability to deal with imprecise and uncertain information, provides a promising framework for addressing the complexities involved in maternal health. By drawing upon various soft computing methodologies like fuzzy logic, neural networks, and genetic algorithms, this research aims to develop a comprehensive system for assessing pregnancy risks. The proposed approach integrates data from diverse sources, including medical records, maternal history, and environmental factors, to improve the accuracy and reliability of risk assessment during pregnancy. Through the soft computing techniques, this study strives to contribute to the early detection and proactive management of potential complications, ultimately leading to better outcomes for both the mother and the fetus.