Enhancing early gestational diabetes mellitus prediction with imputation-based machine learning framework: A comparative study on real-world clinical records

Enhancing early gestational diabetes mellitus prediction with imputation-based machine learning framework: A comparative study on real-world clinical records

Objective Gestational diabetes mellitus (GDM) is one of the most common pregnancy complications. Electronic health records (EHRs) promise GDM risk prediction, but missing data poses a challenge to developing reliable and generalizable risk prediction models. This study aims to address the problem of...

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Bibliographic Details
Main Authors: Leyao Ma, Lin Yang, Yaxin Wang, Jie Hao, Yini Li, Liangkun Ma, Ziyang Wang, Ye Li, Suhan Zhang, Mingyue Hu, Jiao Li, Yin Sun
Format: Article
Language:English
Published: SAGE Publishing 2025-07-01
Series:Digital Health
Online Access:https://doi.org/10.1177/20552076251352436
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