From the Journals

ML Model May Predict Preeclampsia Risk

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

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  • 1

    Study published in JAMA Network Open.

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    Machine learning model predicts preeclampsia risk using EHR data.

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    Involves 58,839 pregnancies from NewYork-Presbyterian hospitals.

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    Model accuracy peaks at approximately 34 weeks gestation.

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    Provides continuous risk updates, suggesting early intervention potential.

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    Highlights importance of blood pressure as a predictor.

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    Requires prospective validation for clinical use.

Original Source(s)

ML Model May Predict Preeclampsia Risk

  • by Olivia Anderson

  • March 18, 2026

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