Machine learning-based prediction of adverse pregnancy outcomes in antiphospholipid syndrome using pregnancy antibody levels

Machine learning-based prediction of adverse pregnancy outcomes in antiphospholipid syndrome using pregnancy antibody levels

BackgroundAntiphospholipid syndrome (APS) is a major immune-related disorder that leads to adverse pregnancy outcomes (APO), including recurrent miscarriage, placental abruption, preterm birth, and fetal growth restriction. Antiphospholipid antibodies (aPLs), particularly anticardiolipin antibodies...

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Bibliographic Details
Main Authors: Wanqing Liu, Ju Huang, Jun Xiao, Shanling Yan
Format: Article
Language:English
Published: Frontiers Media S.A. 2025-08-01
Series:Frontiers in Physiology
Subjects:
antiphospholipid syndrome (APS)
adverse pregnancy outcomes (APO)
machine learning
aβ2GP1
XGBoost
Online Access:https://www.frontiersin.org/articles/10.3389/fphys.2025.1617796/full
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https://www.frontiersin.org/articles/10.3389/fphys.2025.1617796/full

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