The prediction models for the optimal timing of surgical intervention for necrotizing enterocolitis: nomogram vs. five machine learning models.

Journal: Pediatric surgery international
Published Date: Aug 20, 2025

Abstract

BACKGROUND: Necrotizing enterocolitis (NEC) is one of the most common diseases that pose serious threats to the life of newborns. In clinical practice, NEC is typically treated by surgical intervention, but it is still difficult to identify the timing of surgical intervention for this disease. Therefore, this study was conducted to establish a machine learning (ML) model for identifying the optimal timing of surgical intervention for NEC by comparing logistic regression (LR) models with ML models and to visualize important influencing indicators via a nomogram.

Authors

  • Xuetian Li
    Department of Pediatric Surgery, Qilu Hospital of Shandong University, Jinan, China.
  • Liting Zhang
    School of Microelectronics, Faculty of Information Technology, Beijing University of Technology, Beijing, 100124, China.
  • Hongjie Gao
    State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Science, Beijing 100012, China; State Environmental Protection Key Laboratory of Estuarine and Coastal Environment, Chinese Research Academy of Environmental Science, Beijing 100012, China; State Key Laboratory of Pollution Control and Resource Reuse, College of Environmental Science and Engineering, Tongji University, Shanghai, 200092, China. Electronic address: gaohj@craes.org.cn.
  • Yanping Wang
    The First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, Henan, China.
  • Fan Huang
  • Ding Li
    School of Pharmaceutical Sciences, Sun Yat-sen University, Guangzhou, 510006, China.
  • Fengyin Sun
    Department of Pediatric Surgery, Qilu Hospital of Shandong University, Jinan, China. tjcollege2014@163.com.

Keywords

External Resources

Popular Topics
Recent Journals