Predicting perinatal mortality based on maternal health status and health insurance service using homogeneous ensemble machine learning methods.

ABSTRACT:

Background

Perinatal mortality in Ethiopia is the highest in Africa, with 68 per 1000 pregnancies intrapartum deaths. It is mainly associated with home delivery, which contributes to more than 75% of perinatal deaths. Financial constraints significantly impact timely access to maternal health care. Financial incentives, such as health insurance, may address the demand- and supply-side factors. This study, hence, aims to predict perinatal mortality based on maternal health status and health insurance service using homogeneous ensemble machine learning methods.

Methods

The data was collected from the Ethiopian demographic health survey from 2011 to 2019 G.C. The data were pre-processed to get quality data that are suitable for the homogenous ensemble machine-learning algorithm

SUBMITTER: Bogale DS 

PROVIDER: S-EPMC9795949 | biostudies-literature | 2022 Dec

REPOSITORIES: biostudies-literature