A risk prediction model based on machine learning algorithm for parastomal hernia after permanent colostomy.

Journal: BMC medical informatics and decision making
Published Date: Aug 8, 2024

Abstract

OBJECTIVE: To develop a machine learning-based risk prediction model for postoperative parastomal hernia (PSH) in colorectal cancer patients undergoing permanent colostomy, assisting nurses in identifying high-risk groups and devising preventive care strategies.

Authors

  • Tian Dai
    Department of General Surgery (Ward one), The Second Affiliated Hospital of Anhui Medical University, Hefei, Anhui, 230601, China.
  • Manzhen Bao
    Nursing Department, The Second Affiliated Hospital of Anhui Medical University, Hefei, Anhui, 230601, China.
  • Miao Zhang
    gRED Computational Science, Genentech, Inc., South San Francisco, California.
  • Zonggui Wang
    Department of Orthopedics (Ward two), The Second Affiliated Hospital of Anhui Medical University, Hefei, Anhui, 230601, China.
  • Jingjing Tang
    School of Business Administration, Southwestern University of Finance and Economics, Chengdu 611130, China. Electronic address: tangjingjing13@mails.ucas.ac.cn.
  • Zeyan Liu
    Department of Emergency Internal Medicine, The Second Affiliated Hospital of Anhui Medical University, Hefei, Anhui, 230601, China. jy02893741@163.com.

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