Development and preliminary evaluation of a machine learning model for predicting low birth weight using placental IVIM-MRI and maternal clinical characteristics

Placental IVIM MRI f values from distinct placental regions are significant LBW predictors. The model provides accurate prenatal risk assessment, guiding early interventions to optimize perinatal outcomes.

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Publication Details

Journal
European Journal of Obstetrics & Gynecology and Reproductive Biology
Published
2025-12-31
DOI
https://doi.org/10.1016/j.ejogrb.2025.114930
Primary Topic
Fetal and Pediatric Neurological Disorders
Type
article
Field-Weighted Citation Impact
0.00
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article

Development and preliminary evaluation of a machine learning model for predicting low birth weight using placental IVIM-MRI and maternal clinical characteristics

Wei Bian, Yuan Yao, Wenting Zhang, Hui Liu et al.
European Journal of Obstetrics & Gynecology and Reproductive Biology
Fetal and Pediatric Neurological Disorders
article

Development and preliminary evaluation of a machine learning model for predicting low birth weight using placental IVIM-MRI and maternal clinical characteristics

Wei Bian, Yuan Yao, Wenting Zhang, Hui Liu, Fang Wei, Linping Wang
article en

Abstract

Placental IVIM MRI f values from distinct placental regions are significant LBW predictors. The model provides accurate prenatal risk assessment, guiding early interventions to optimize perinatal outcomes.

European Journal of Obstetrics & Gynecology and Reproductive BiologyVol. 318
First Hospital of Jiaxing (CN)
Openalex Percentile: Top 17%
Fetal and Pediatric Neurological Disorders
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