Machine learning-based risk factor analysis of adverse birth outcomes in very low birth weight infants

Machine learning-based risk factor analysis of adverse birth outcomes in very low birth weight infants

Abstract This study aimed to analyze major predictors of adverse birth outcomes in very low birth weight (VLBW) infants including particulate matter concentration (PM10), using machine learning and the national prospective cohort. Data consisted of 10,423 VLBW infants from the Korean Neonatal Networ...

Full description

Bibliographic Details
Main Authors: Hannah Cho, Eun Hee Lee, Kwang-Sig Lee, Ju Sun Heo
Format: Article
Language:English
Published: Nature Portfolio 2022-10-01
Series:Scientific Reports
Online Access:https://doi.org/10.1038/s41598-022-16234-y

Internet

https://doi.org/10.1038/s41598-022-16234-y

Similar Items