Machine learning algorithms to predict epidural-related maternal fever: a retrospective study

Optimally applying logistic regression models can enable rapid and straightforward identification of ERMF risk and the implementation of rational therapeutic measures, in contrast to machine learning models.

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Publication Details

Journal
Frontiers in Pharmacology
Published
2025-06-11
DOI
https://doi.org/10.3389/fphar.2025.1614770
Citations
2
Primary Topic
Preterm Birth and Chorioamnionitis
Type
article
Field-Weighted Citation Impact
2.71
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article

Machine learning algorithms to predict epidural-related maternal fever: a retrospective study

Hongliang Mei, Haixia Zhang, Xiaohui Guo
2 citations
Frontiers in Pharmacology
Preterm Birth and Chorioamnionitis
2.71
article

Machine learning algorithms to predict epidural-related maternal fever: a retrospective study

Hongliang Mei, Haixia Zhang, Xiaohui Guo
article en
2 citations

Abstract

Optimally applying logistic regression models can enable rapid and straightforward identification of ERMF risk and the implementation of rational therapeutic measures, in contrast to machine learning models.

Frontiers in PharmacologyVol. 16
Hainan Modern Women and Children's Hospital (CN), Nanjing Drum Tower Hospital (CN), Hainan Medical University (CN), Nanjing Medical University (CN)
Openalex Percentile: Top 10%
Preterm Birth and Chorioamnionitis
2.71
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