Optimizing predictive features using machine learning for early miscarriage risk following single vitrified-warmed blastocyst transfer

Optimizing predictive features using machine learning for early miscarriage risk following single vitrified-warmed blastocyst transfer

Research questionCan machine learning models accurately predict the risk of early miscarriage following single vitrified-warmed blastocyst transfer (SVBT)?DesignA dual-center retrospective analysis of 1,664 SVBT cycles, including 308 early miscarriage cases, was conducted across two reproductive cen...

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Bibliographic Details
Main Authors: Lidan Liu, Bo Liu, Huimei Wu, Qiuying Gan, Qianyi Huang, Mujun Li
Format: Article
Language:English
Published: Frontiers Media S.A. 2025-04-01
Series:Frontiers in Endocrinology
Subjects:
early miscarriage
single vitrified-warmed blastocyst transfer (SVBT)
machine learning (ML)
voting classifier
gradient boosting
Online Access:https://www.frontiersin.org/articles/10.3389/fendo.2025.1557667/full
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https://www.frontiersin.org/articles/10.3389/fendo.2025.1557667/full

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