Prediction of gestational diabetes mellitus at the first trimester: machine-learning algorithms.

Journal: Archives of gynecology and obstetrics
Published Date: Jun 1, 2024

Abstract

PURPOSE: Short- and long-term complications of gestational diabetes mellitus (GDM) involving pregnancies and offspring warrant the development of an effective individualized risk prediction model to reduce and prevent GDM together with its associated co-morbidities. The aim is to use machine learning (ML) algorithms to study data gathered throughout the first trimester in order to predict GDM.

Authors

  • Yi-Xin Li
    Department of Obstetrics and Gynecology, Xinhua Hospital Chongming Branch, School of Medicine, Shanghai Jiao Tong University, Shanghai, China.
  • Yi-Chen Liu
    Department of Nephrology, Chongming Hospital Affiliated to Shanghai University of Medicine and Health Sciences (Xinhua Hospital Chongming Branch), Shanghai, China.
  • Mei Wang
    Natural Products Utilization Research Unit, Agricultural Research Service, U.S. Department of Agriculture, Oxford, MS, 38677, USA.
  • Yu-Li Huang
    Department of Obstetrics and Gynecology, Chongming Hospital Affiliated to Shanghai University of Medicine and Health Sciences (Xinhua Hospital Chongming Branch), Shanghai, China. 977471668@qq.com.

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