Machine learning model-based preterm birth prediction and clinical nomogram: A big retrospective cohort study.

Journal: International journal of gynaecology and obstetrics: the official organ of the International Federation of Gynaecology and Obstetrics
PMID: 39552525

Abstract

OBJECTIVE: This study sought to develop a multifactorial predictive model for preterm birth risk, with the goal of providing clinical practitioners with early prevention.

Authors

  • Ya Liu
    Department of Electrical Automation, Hebei University of Water Resources and Electric Engineering, Cangzhou 061001, China.
  • Jiangling Liu
    State Key Laboratory of Vaccines for Infectious Diseases, Xiang An Biomedicine Laboratory and State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen University, Xiamen, China.
  • Heqing Shen
    Key Lab of Urban Environment and Health, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen, China.

Keywords

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