Development and validation of a machine-learning model for preoperative risk of gastric gastrointestinal stromal tumors.

Journal: Journal of gastrointestinal surgery : official journal of the Society for Surgery of the Alimentary Tract
PMID: 39448018

Abstract

BACKGROUND: Gastrointestinal stromal tumors (GISTs) have malignant potential, and treatment varies according to risk. However, no specific protocols exist for preoperative assessment of the malignant potential of gastric GISTs (gGISTs). This study aimed to use machine learning (ML) to develop and validate clinically relevant preoperative models to predict the malignant potential of gGISTs.

Authors

  • Shi-Qi Liang
    Department of Gastroenterology, Affiliated Hospital of North Sichuan Medical College, Nanchong, Sichuan, China.
  • Yu-Tong Cui
    Department of Gastroenterology, Affiliated Hospital of North Sichuan Medical College, Nanchong, Sichuan, China.
  • Guang-Bing Hu
    Department of Gastroenterology, Affiliated Hospital of North Sichuan Medical College, Nanchong, Sichuan, China.
  • Hai-Yang Guo
    Department of Gastroenterology, Affiliated Hospital of North Sichuan Medical College, Nanchong, Sichuan, China.
  • Xin-Rui Chen
    Department of Gastroenterology, Affiliated Hospital of North Sichuan Medical College, Nanchong, Sichuan, China.
  • Ji Zuo
    Department of Gastroenterology, Affiliated Hospital of North Sichuan Medical College, Nanchong, Sichuan, China.
  • Zhi-Rui Qi
    Department of Gastroenterology, Affiliated Hospital of North Sichuan Medical College, Nanchong, Sichuan, China.
  • Xian-Fei Wang
    Department of Gastroenterology, Affiliated Hospital of North Sichuan Medical College, Nanchong, Sichuan, China; Digestive Endoscopy Center, Affiliated Hospital of North Sichuan Medical College, Nanchong, Sichuan, China. Electronic address: 2750853458@qq.com.

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