Application of Machine Learning Approaches to Predict Postnatal Growth Failure in Very Low Birth Weight Infants

PURPOSE: The aims of the study were to develop and evaluate a machine learning model with which to predict postnatal growth failure (PGF) among very low birth weight (VLBW) infants. MATERIALS AND METHODS: Of 10425 VLBW infants registered in the Korean Neonatal Network between 2013 and 2017, 7954 inf...

Descripción completa

Detalles Bibliográficos
Autores principales: Han, Jung Ho, Yoon, So Jin, Lee, Hye Sun, Park, Goeun, Lim, Joohee, Shin, Jeong Eun, Eun, Ho Seon, Park, Min Soo, Lee, Soon Min
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Yonsei University College of Medicine 2022
Materias:
Original Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9226835/
https://www.ncbi.nlm.nih.gov/pubmed/35748075
http://dx.doi.org/10.3349/ymj.2022.63.7.640

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9226835/
https://www.ncbi.nlm.nih.gov/pubmed/35748075
http://dx.doi.org/10.3349/ymj.2022.63.7.640

Ejemplares similares