Comparison of Machine Learning Models and the FMF Competing-Risks Algorithm for First-Trimester Preeclampsia Screening in a Romanian Cohort

<b>Background/Objectives</b>: First-trimester preeclampsia (PE) screening is most widely implemented using the Fetal Medicine Foundation (FMF) algorithm, which combines maternal factors with biophysical and biochemical markers via a competing-risks/Bayes framework to produce individualized risks and...

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Autors principals:	Alexandra-Elena Cristofor, Alexandru Carauleanu, Ingrid-Andrada Vasilache, Iustina Condriuc, Ovidiu Bica, Dragos Nemescu
Format:	Artigo
Idioma:	Inglês
Publicat:	MDPI AG 2026-05-01
Col·lecció:	Diagnostics
Matèries:	preeclampsia first trimester screening Bayes theorem logistic regression random forest XGBoost
Accés en línia:	https://www.mdpi.com/2075-4418/16/10/1540
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