ML Model Predicts Third-Trimester Preeclampsia Risk

Weill Cornell Medicine investigators publish March 6 in JAMA Network Open a machine-learning model that continuously predicts short-term preeclampsia risk using electronic health record data collected late in pregnancy. Trained on 35,895 deliveries and evaluated across nearly 59,000 pregnancies at three NewYork-Presbyterian hospitals, the model best predicts risk around 34 weeks and may give clinicians lead time for monitoring and delivery planning.