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

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

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Detalles Bibliográficos
Autores principales: Cho, Hannah, Lee, Eun Hee, Lee, Kwang-Sig, Heo, Ju Sun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9526718/
https://www.ncbi.nlm.nih.gov/pubmed/36183001
http://dx.doi.org/10.1038/s41598-022-16234-y

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9526718/
https://www.ncbi.nlm.nih.gov/pubmed/36183001
http://dx.doi.org/10.1038/s41598-022-16234-y

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