Methodological conduct and risk of bias in studies on prenatal birthweight prediction models using machine learning techniques: a systematic review.

Journal: BMC pregnancy and childbirth
Published Date: Jul 2, 2025

Abstract

OBJECTIVE: To assess the methodological quality and the risk of bias, of studies that developed prediction models using Machine Learning (ML) techniques to estimate prenatal birthweight.

Authors

  • Jing Gao
    Department of Gastroenterology 3, Hubei University of Medicine, Renmin Hospital, Shiyan, Hubei, China.
  • Yujun Yao
    Shanghai Artificial Intelligence Laboratory, Shanghai, 200030, China.
  • Jingdong Xue
    Department of Urology, School of Medicine, Tongji Hospital, Tongji University, Shanghai, 200030, China.
  • Ruiyao Chen
    Shanghai Artificial Intelligence Laboratory, Shanghai, China.
  • Xingyu Yang
    School of Biological Sciences, Georgia Institute of Technology, Atlanta, Georgia, United States of America.
  • Jie Xu
    Second Affiliated Hospital Zhejiang University School of Medicine, Hangzhou, Zhejiang Province 310000, China.
  • Weiwei Cheng
    International Peace Maternity and Child Health Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, 200030, China. wwcheng29@shsmu.edu.cn.

Keywords

External Resources

Popular Topics
Recent Journals