A machine learning-based framework for predicting postpartum chronic pain: a retrospective study.

Journal: BMC medical informatics and decision making
PMID: 40247305

Abstract

BACKGROUND: Postpartum chronic pain is prevalent, affecting many women after delivery. Machine learning algorithms have been widely used in predicting postoperative conditions. We investigated the prevalence of and risk factors for postpartum chronic pain, and aimed to develop a machine learning model for its prediction.

Authors

  • Fan Liu
    Hunan Provincial Key Laboratory of Dong Medicine, Hunan University of Medicine, Huaihua, China.
  • Ting Li
    Institute of Biomedical Engineering, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
  • Dongxu Zhou
    Institution of Neuroscience and Brain Disease, Department of Anesthesiology, Xiangyang Central Hospital, Affiliated Hospital of Hubei University of Arts and Science, No 136, Jingzhou Street, Xiangcheng District, Xiangyang, Hubei, 441000, China.
  • Shengnan Shi
    Institution of Neuroscience and Brain Disease, Department of Anesthesiology, Xiangyang Central Hospital, Affiliated Hospital of Hubei University of Arts and Science, No 136, Jingzhou Street, Xiangcheng District, Xiangyang, Hubei, 441000, China.
  • Xingrui Gong
    Institution of Neuroscience and Brain Disease, Department of Anesthesiology, Xiangyang Central Hospital, Affiliated Hospital of Hubei University of Arts and Science, No 136, Jingzhou Street, Xiangcheng District, Xiangyang, Hubei, 441000, China. gongxrhbxy@sohu.com.

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