Machine Learning Estimation of Gestational Age at Delivery Using Linked Mother-Infant Electronic Health Records Across Two Health Systems
This study demonstrates that supervised machine learning models trained on linked mother-infant electronic health records can accurately and generalizably estimate gestational age at delivery across different health systems, providing a robust framework to support large-scale maternal and neonatal health research.