A Machine Learning Based Web Application for Pre-Eclampsia Risk Prediction, Awareness and Management
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Date
2025-05-06
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Uganda Christian University
Abstract
Pre-eclampsia is a critical condition affecting pregnant women that is
characterized by high blood pressure and potential damage to vital organs. This
research focuses on developing a machine learning-based web application
designed to predict the risk of pre-eclampsia, enhance awareness and provide
management strategies. Utilizing patient data, the application aims to offer
accurate predictions and a recommendation. The project involves data collection,
model training and application deployment emphasizing the integration of user-
friendly interfaces and real-time data processing. The research underscores the
importance of early detection and intervention potentially reducing the adverse
outcomes associated with pre-eclampsia. By leveraging machine learning
algorithms and web technologies, this application aspires to empower healthcare
providers and expectant mothers with actionable insights fostering better health
outcomes and informed decision-making. This work represents a significant stride
towards improving maternal health care through innovative technological
solutions.
Description
Undergraduate research