Distributed Big Data Analytics Method for the Early Prediction of the Neonatal 5-Minute Apgar Score before or during Birth and Ranking the Risk Factors from a National Dataset

One-minute and five-minute Apgar scores are good measures to assess the health status of newborns. A score can predict risk some disorders such as asphyxia, encephalopathy, cerebral palsy ADHD. The early prediction before or during birth ranking factors be helpful manage reduce probability producing low scores. Therefore, main aim this study is neonate 5-min for a big national dataset using data analytics methods. In study, including 60 features describing cases registered in Iranian maternal neonatal (IMAN) registry from 1 April 2016 January 2017 collected. distributed method feature predictors proposed study. provide ability with by analyzing that describe prenatal properties birth. top 14 were identified used training classifiers. Our stack ensemble outperforms compared classifiers an accuracy 99.37 ± 1.06, precision recall 99.50 0.61 F-score 99.41 0.70 (for confidence interval 95%) low, moderate high Among predictors, fetal height around baby’s head weight denote growth status. Fetal restrictions lead score. Moreover, hospital type medical science university healthcare system-related managed via improving quality services all over country.