Cargando…
Machine learning-based risk factor analysis of necrotizing enterocolitis in very low birth weight infants
This study used machine learning and a national prospective cohort registry database to analyze the major risk factors of necrotizing enterocolitis (NEC) in very low birth weight (VLBW) infants, including environmental factors. The data consisted of 10,353 VLBW infants from the Korean Neonatal Netwo...
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: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9741654/ https://www.ncbi.nlm.nih.gov/pubmed/36496465 http://dx.doi.org/10.1038/s41598-022-25746-6 |
Ejemplares similares
-
Machine learning-based risk factor analysis of adverse birth outcomes in very low birth weight infants
por: Cho, Hannah, et al.
Publicado: (2022) -
Necrotizing Enterocolitis among Very-Low-Birth-Weight Infants in Korea
por: Youn, Young Ah, et al.
Publicado: (2015) -
Necrotizing Enterocolitis in Very Low Birth Weight Infants: A Systemic Review
por: Patel, Bhoomika K., et al.
Publicado: (2012) -
The effect of daily probiotics on the incidence and severity of necrotizing enterocolitis in infants with very low birth weight
por: Que, Jessica, et al.
Publicado: (2021) -
The Role of Immunonutrients in the Prevention of Necrotizing Enterocolitis in Preterm Very Low Birth Weight Infants
por: Zhou, Ping, et al.
Publicado: (2015)