A machine learning approach to estimating preterm infants survival: development of the Preterm Infants Survival Assessment (PISA) predictor.

ABSTRACT: Estimation of mortality risk of very preterm neonates is carried out in clinical and research settings. We aimed at elaborating a prediction tool using machine learning methods. We developed models on a cohort of 23747 neonates <30 weeks gestational age, or <1501 g birth weight, enrolled in the Italian Neonatal Network in 2008-2014 (development set), using 12 easily collected perinatal variables. We used a cohort from 2015-2016 (N = 5810) as a test set. Among several machine learning methods we chose artificial Neural Networks (NN). The resulting predictor was compared with logistic regression models. In the test cohort, NN had a slightly better discrimination than logistic regression (P < 0.002). The differences were greater in subgroups of neonates (at various gestational age or birth we

SUBMITTER: Podda M 

PROVIDER: S-EPMC6137213 | biostudies-literature | 2018 Sep

REPOSITORIES: biostudies-literature