Back to Search
Journal ArticleOpen Access

Predicting risks of low birth weight in Bangladesh with machine learning

Author Affiliations
Khulna University, Jatiya Kabi Kazi Nazrul Islam University
Published InPLoS ONE
Year2022
Citations72

Abstract

BACKGROUND AND OBJECTIVE: Low birth weight is one of the primary causes of child mortality and several diseases of future life in developing countries, especially in Southern Asia. The main objective of this study is to determine the risk factors of low birth weight and predict low birth weight babies based on machine learning algorithms. MATERIALS AND METHODS: Low birth weight data has been taken from the Bangladesh Demographic and Health Survey, 2017-18, which had 2351 respondents. The risk factors associated with low birth weight were investigated using binary logistic regression. Two machine learning-based classifiers (logistic regression and decision tree) were adopted to characterize and predict low birth weight. The model performances were evaluated by accuracy, sensitivity, specificity, positive predictive…
View at Publisher

BORR does not host full-text PDFs. The button above takes you to the original publisher.