This study investigates the use of machine learning algorithms to predict high-risk pregnancies, analyzing health data from over 1000 pregnant women in Bangladesh.

The research compares six different algorithms, finding that the Multilayer Perceptron (MLP) model outperforms the others, achieving high accuracy, especially for high-risk predictions.

The paper highlights the MLP model's ability to quickly process data and its potential as a tool for medical professionals to improve maternal health management by enabling early identification and intervention in high-risk cases.