Prediction of postpartum depression in women: development and validation of multiple machine learning models.

Journal: Journal of translational medicine
PMID:

Abstract

BACKGROUND: Postpartum depression (PPD) is a significant public health issue. This study aimed to develop and validate machine learning (ML) models using biopsychosocial predictors to predict the risk of PPD for perinatal women and to provide several risk assessment tools for the early detection of PPD.

Authors

  • Weijing Qi
    Humanistic Care and Health Management Innovation Center, School of Nursing, Hebei Medical University, 361 East Zhongshan Road, Shijiazhuang, 050017, Hebei, China.
  • Yongjian Wang
    Humanistic Care and Health Management Innovation Center, School of Nursing, Hebei Medical University, 361 East Zhongshan Road, Shijiazhuang, 050017, Hebei, China.
  • Yipeng Wang
    Beijing Obstetrics and Gynecology Hospital, Capital Medical University, Beijing Maternal and Child Health Care Hospital, Beijing 100026, P. R. China.
  • Sha Huang
    School of Intelligent Medicine, Chengdu University of Traditional Chinese Medicine, Chengdu, 611137, Sichuan, China. Electronic address: huangsha1pot26@126.com.
  • Cong Li
    Key Laboratory of Synthetic and Natural Functional Molecule Chemistry of Ministry of Education, College of Chemistry and Materials Science, National Demonstration Center for Experimental Chemistry Education, Northwest University, Xi'an, Shaanxi 710127, China. Electronic address: licong@nwu.edu.cn.
  • Haoyu Jin
    Humanistic Care and Health Management Innovation Center, School of Nursing, Hebei Medical University, 361 East Zhongshan Road, Shijiazhuang, 050017, Hebei, China.
  • Jinfan Zuo
    Humanistic Care and Health Management Innovation Center, School of Nursing, Hebei Medical University, 361 East Zhongshan Road, Shijiazhuang, 050017, Hebei, China.
  • Xuefei Cui
    Humanistic Care and Health Management Innovation Center, School of Nursing, Hebei Medical University, 361 East Zhongshan Road, Shijiazhuang, 050017, Hebei, China.
  • Ziqi Wei
    CAS Key Laboratory of Molecular Imaging, Institute of Automation, Chinese Academy of Sciences, Beijing, People's Republic of China.
  • Qing Guo
    Department of Dermatology, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou, China.
  • Jie Hu
    Corteva Agriscience, Farming Solutions and Digital, Indianapolis, IN, United States.