Predicting Gestational Diabetes Mellitus in the first trimester using machine learning algorithms: a cross-sectional study at a hospital fertility health center in Iran.

Journal: BMC medical informatics and decision making
PMID: 39754258

Abstract

BACKGROUND: Gestational Diabetes Mellitus (GDM) is a common complication during pregnancy. Late diagnosis can have significant implications for both the mother and the fetus. This research aims to create an early prediction model for GDM in the first trimester of pregnancy. This model will help obstetricians and gynecologists make appropriate decisions for treating and preventing GDM complications.

Authors

  • Somayeh Kianian Bigdeli
    Department of Health Information Management, School of Allied Medical Sciences, Tehran University of Medical Sciences, Tehran, Iran.
  • Marjan Ghazisaedi
    Department of Health Information Management, School of Allied Medical Sciences, Tehran University of Medical Sciences, Tehran, Iran. ghazimar@tums.ac.ir.
  • Seyed Mohammad Ayyoubzadeh
    Department of Health Information Management, School of Allied Medical Sciences, Tehran University of Medical Sciences, Tehran, Iran.
  • Sedigheh Hantoushzadeh
    Vali-E-Asr Reproductive Health Research Center, Family Health Research Institute, Imam Khomeini Hospital Complex, Tehran University of Medical Sciences, Tehran, Iran.
  • Marjan Ahmadi
    Department of Obstetrics and Gynecology, Tehran University of Medical Sciences, Tehran, Iran.

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