Data-driven risk stratification for preterm birth in Brazil: development of a machine learning based innovation for health care

Causes and performing early identifying the preventable risk stratification of pregnant women are instrumental to develop strategies to prevent and reduce preterm birth (PTB). The study aims to combine different national level data sources to understand the main predictors of PTB and develop a machine-learning–based predictive model to conduct automated risk stratification at the point of care level, integrated with advanced data visualization for clinical decision support.