Predicting maternal risk level using machine learning models.

ABSTRACT:

Background

Maternal morbidity and mortality remain critical health concerns globally. As a result, reducing the maternal mortality ratio (MMR) is part of goal 3 in the global sustainable development goals (SDGs), and previously, it was an important indicator in the Millennium Development Goals (MDGs). Therefore, identifying high-risk groups during pregnancy is crucial for decision-makers and medical practitioners to mitigate mortality and morbidity. However, the availability of accurate predictive models for maternal mortality and maternal health risks is challenging. Compared with traditional predictive models, machine learning algorithms have emerged as promising predictive modelling methods providing accurate predictive models.

Methods

This work aims to explore the potent

SUBMITTER: Al Mashrafi SS 

PROVIDER: S-EPMC11657143 | biostudies-literature | 2024 Dec

REPOSITORIES: biostudies-literature