First-Trimester Machine Learning to Predict Preeclampsia in Normotensive Pregnancies by American Heart Association Guidelines
Abstract
Objective: This study aimed to determine whether unsupervised machine learning can identify phenotypically distinct subgroups at increased risk for preeclampsia among pregnant individuals with American Heart Association (AHA)-defined normal blood pressure in the first trimester. Methods: weeks' gestation at two academic centers. Participants with prepregnancy chronic hypertension or major fetal/placental abnormalities were excluded. First-trimester blood pressure was categorized using the 2017 AHA guidelines. Among individuals with AHA-defined normal blood pressure (
Fields of Study & Subjects
Pregnancy and preeclampsia studies
Neurological Complications and Syndromes
Blood Pressure and Hypertension Studies
Publication details
- Journal / source
- American Journal of Perinatology
- Volume
- 43
- Issue
- 11
- Pages
- 1472–1478
- Publication date
- 12 January 2026
- Language
- EN