Development and validation of machine learning models and nomograms for predicting the surgical difficulty of laparoscopic resection in rectal cancer.

Journal: World journal of surgical oncology
PMID:

Abstract

BACKGROUND: The objective of this study is to develop and validate a machine learning (ML) prediction model for the assessment of laparoscopic total mesorectal excision (LaTME) surgery difficulty, as well as to identify independent risk factors that influence surgical difficulty. Establishing a nomogram aims to assist clinical practitioners in formulating more effective surgical plans before the procedure.

Authors

  • Xiangyong Li
    Department of Gastrointestinal Surgery, The Second Affiliated Hospital of Soochow University, Suzhou City, Jiangsu Province, People's Republic of China.
  • Zeyang Zhou
    Department of Gastrointestinal Surgery, The Second Affiliated Hospital of Soochow University, Suzhou City, Jiangsu Province, People's Republic of China.
  • Bing Zhu
    Department of Gynecology, the First People's Hospital of Shangqiu, Shangqiu, Henan, People's Republic of China.
  • Yong Wu
    Department of Gastrointestinal Surgery, The Second Affiliated Hospital of Soochow University, Suzhou City, Jiangsu Province, People's Republic of China.
  • Chungen Xing
    Department of Gastrointestinal Surgery, The Second Affiliated Hospital of Soochow University, Suzhou City, Jiangsu Province, People's Republic of China.