Predicting the Need for Cardiopulmonary Resuscitation in Preterm Infants in the Delivery Room Using Machine Learning Models: Analysis of a Korean Neonatal Network Database

Hyun-Ho Kim

Predicting the Need for Cardiopulmonary Resuscitation in Preterm Infants in the Delivery Room Using Machine Learning Models: Analysis of a Korean Neonatal Network Database

Hyun-Ho Kim

Department of Medicine

Research output: Contribution to journal › Journal article › peer-review

Original language	Korean
Journal	Journal of Korean Medical Science
State	Published - 2025.09.1

Cite this

@article{911d0ba2cf7241c58cb7d95047a8f408,

title = "Predicting the Need for Cardiopulmonary Resuscitation in Preterm Infants in the Delivery Room Using Machine Learning Models: Analysis of a Korean Neonatal Network Database",

author = "Hyun-Ho Kim",

year = "2025",

month = sep,

day = "1",

language = "Korean",

journal = "Journal of Korean Medical Science",

issn = "1011-8934",

}