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

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第一作者： Leyao,Ma

第一单位： Institute of Medical Information, Chinese Academy of Medical Science & Peking Union Medical College, Beijing, China.

作者： Leyao,Ma ^[1] ; Lin,Yang ^[2] ; Yaxin,Wang ^[3] ; Jie,Hao ^[1] ; Yini,Li ^[4] ; Liangkun,Ma ^[4] ; Ziyang,Wang ^[1] ; Ye,Li ^[4] ; Suhan,Zhang ^[4] ; Mingyue,Hu ^[4] ; Jiao,Li ^[2] ; Yin,Sun ^[4]

作者单位： Institute of Medical Information, Chinese Academy of Medical Science & Peking Union Medical College, Beijing, China. ^[1] Institute of Medical Information, Chinese Academy of Medical Science & Peking Union Medical College, Beijing, China.;Key Laboratory of Medical Information Intelligent Technology, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China. ^[2] The Obstetrics and Gynecology Hospital of Fudan University, Shanghai, China. ^[3] National Clinical Research Center for Obstetric & Gynecologic Diseases, Department of Obstetrics and Gynecology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China. ^[4]

关键词 Gestational diabetes mellitus electronic health records imputation machine learning missing data risk prediction

DOI 10.1177/20552076251352436

PMID 40755962

发布时间 2025-08-06

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

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

Digital health

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