Machine Learning Algorithms Versus Classical Regression Models in Pre-Eclampsia Prediction: A Systematic Review.
Tiruneh SA, Vu TTT, Rolnik DL, Teede HJ, Enticott J.
Tiruneh SA, et al.
Curr Hypertens Rep. 2024 May 28. doi: 10.1007/s11906-024-01297-1. Online ahead of print.
Curr Hypertens Rep. 2024.
PMID: 38806766
Review.
The most frequent prognostic factors were age, pre-pregnancy body mass index, chronic medical conditions, parity, prior history of pre-eclampsia, mean arterial pressure, uterine artery pulsatility index, placental growth factor, and pregnancy-associated plasma …
The most frequent prognostic factors were age, pre-pregnancy body mass index, chronic medical conditions, parity, prior history of pre-eclam …