Application of machine learning algorithms to predict postoperative surgical site infections and surgical site occurrences following inguinal hernia surgery.

Journal: Hernia : the journal of hernias and abdominal wall surgery
PMID: 39287831

Abstract

PURPOSE: This study aimed to develop, validate, and evaluate machine learning (ML) algorithms for predicting Surgical site infections (SSI) and surgical site occurrences (SSO) after elective open inguinal hernia surgery.

Authors

  • Qian Wu
    China Electric Power Research Institute, Beijing, China.
  • Hekai Shi
    Department of General Surgery, Fudan University Affiliated Huadong Hospital, 221 Yan'an West Road, Jing'an District, Shanghai, 200040, China.
  • Heng Song
    Department of General Surgery, Fudan University Affiliated Huadong Hospital, 221 Yan'an West Road, Jing'an District, Shanghai, 200040, China.
  • Xiaoyu Peng
    Department of General Surgery, Fudan University Affiliated Huadong Hospital, 221 Yan'an West Road, Jing'an District, Shanghai, 200040, China.
  • Jianjun Yang
    Department of Anesthesiology, Pain and Perioperative Medicine, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, China.
  • Yan Gu
    Department of Radiology, The First People's Hospital of Lianyungang, Lianyungang Clinical College of Nanjing Medical University, Lianyungang, China.

Keywords

External Resources

Popular Topics
Recent Journals