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

Ensemble machine learning models, particularly the Voting Classifier and Gradient Boosting Classifier, significantly improve the prediction of early miscarriage following SVBT. These models provide accurate, individualized risk assessments, enhancing clinical decision-making and advancing personalized care in ART.

Authors

Mujun Li (ORCID: https://orcid.org/0000-0003-4475-0033)
Lidan Liu (ORCID: https://orcid.org/0000-0002-0369-8200)
Huimei Wu (ORCID: https://orcid.org/0000-0001-8149-6674)
Qiuying Gan
Qianyi Huang
Bo Liu (ORCID: https://orcid.org/0000-0002-6697-9528)

Institutions

Guangxi Medical University (CN)
First Affiliated Hospital of GuangXi Medical University (CN)
Guangxi Maternal and Child Health Hospital (CN)

Publication Details

Journal: Frontiers in Endocrinology
Published: 2025-04-16
DOI: https://doi.org/10.3389/fendo.2025.1557667
Citations: 3
Primary Topic: Assisted Reproductive Technology and Twin Pregnancy
Type: article
Field-Weighted Citation Impact: 10.48

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article

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

Mujun Li, Lidan Liu, Huimei Wu, Qiuying Gan et al.

Apr 16, 2025

3 citations

Frontiers in Endocrinology

Assisted Reproductive Technology and Twin Pregnancy

10.48

article

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

Mujun Li, Lidan Liu, Huimei Wu, Qiuying Gan, Qianyi Huang, Bo Liu

April 16, 2025article en

3 citations

Abstract

Ensemble machine learning models, particularly the Voting Classifier and Gradient Boosting Classifier, significantly improve the prediction of early miscarriage following SVBT. These models provide accurate, individualized risk assessments, enhancing clinical decision-making and advancing personalized care in ART.

Frontiers in EndocrinologyVol. 16

Guangxi Medical University (CN), First Affiliated Hospital of GuangXi Medical University (CN), Guangxi Maternal and Child Health Hospital (CN)

Openalex Percentile: Top 2%

Assisted Reproductive Technology and Twin Pregnancy

10.48

DOI Open Access PDF OpenAlex

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