Infant birth weight estimation and low birth weight classification in United Arab Emirates using machine learning algorithms.

ABSTRACT: Accurate prediction of a newborn's birth weight (BW) is a crucial determinant to evaluate the newborn's health and safety. Infants with low BW (LBW) are at a higher risk of serious short- and long-term health outcomes. Over the past decade, machine learning (ML) techniques have shown a successful breakthrough in the field of medical diagnostics. Various automated systems have been proposed that use maternal features for LBW prediction. However, each proposed system uses different maternal features for LBW classification and estimation. Therefore, this paper provides a detailed setup for BW estimation and LBW classification. Multiple subsets of features were combined to perform predictions with and without feature selection techniques. Furthermore, the synthetic minority oversampling techni

SUBMITTER: Khan W 

PROVIDER: S-EPMC9287292 | biostudies-literature | 2022 Jul

REPOSITORIES: biostudies-literature