Construction of a Prediction Model for Adverse Perinatal Outcomes in Foetal Growth Restriction Based on a Machine Learning Algorithm: A Retrospective Study.

Journal: BJOG : an international journal of obstetrics and gynaecology
Published Date: May 23, 2025

Abstract

OBJECTIVE: To create and validate a machine learning (ML)-based model for predicting the adverse perinatal outcome (APO) in foetal growth restriction (FGR) at diagnosis.

Authors

  • Xiangli Meng
    Beijing Obstetrics and Gynecology Hospital, Capital Medical University, Beijing, China.
  • Lei Wang
    Department of Nursing, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing, China.
  • Minghui Wu
    Department of Radiology, Henan Provincial People's Hospital, China.
  • Na Zhang
    Department of Nutrition and Food Hygiene, School of Public Health, Peking University, Beijing, China.
  • Xiaofei Li
    Department of Infectious Diseases, YiWu Central Hospita, Zhejiang, 322000, China. Electronic address: xiaofeil2021@163.com.
  • Qingqing Wu
    Beijing Obstetrics and Gynecology Hospital, Capital Medical University. Beijing Maternal and Child Health Care Hospital, China.

Keywords

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