Published on in Vol 21, No 11 (2019): November

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/14738, first published .
Performance of Fetal Medicine Foundation Software for Pre-Eclampsia Prediction Upon Marker Customization: Cross-Sectional Study

Performance of Fetal Medicine Foundation Software for Pre-Eclampsia Prediction Upon Marker Customization: Cross-Sectional Study

Performance of Fetal Medicine Foundation Software for Pre-Eclampsia Prediction Upon Marker Customization: Cross-Sectional Study

Journals

  1. Marić I, Tsur A, Aghaeepour N, Montanari A, Stevenson D, Shaw G, Winn V. Early prediction of preeclampsia via machine learning. American Journal of Obstetrics & Gynecology MFM 2020;2(2):100100 View
  2. Papatheodorou S, Yao W, Vieira C, Li L, Wylie B, Schwartz J, Koutrakis P. Residential radon exposure and hypertensive disorders of pregnancy in Massachusetts, USA: A cohort study. Environment International 2021;146:106285 View