A machine-learning model developed by Weill Cornell Medicine investigators may provide clinicians with an early warning of a complication that can occur late in pregnancy. Preeclampsia is a sudden onset condition that involves high blood pressure prior to delivery. It affects about 2% to 8% of pregnancies worldwide and can have serious consequences for both parent and child. A new study, published March 6 in JAMA Network Open, describes a machine-learning-based computer model that provides continually updated predictions of preeclampsia risk based on electronic health record data recorded late in pregnancy.
This article was originally published on MedicalXpress.com
