From the Journals

ML Model May Predict Preeclampsia Risk

Dynamic EHR-based approach may enable earlier intervention in late pregnancy.

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A recent cohort study published in JAMA Network Open highlights a machine learning model that predicts short-term risk of preeclampsia during late pregnancy using electronic health record data. The study, involving 58,839 pregnancies at NewYork-Presbyterian hospitals, demonstrated that models utilizing easily accessible clinical data can estimate the risk of preeclampsia onset within one to four weeks. The model's accuracy is highest around 34 weeks of gestation, provides continuous risk updates, and shows potential for early intervention, although further prospective validation is needed.

Original Source(s)

ML Model May Predict Preeclampsia Risk

  • by Olivia Anderson

  • March 18, 2026

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