Application of machine learning methods for predicting esophageal variceal bleeding in patients with cirrhosis.

Journal: European radiology
PMID: 39708084

Abstract

OBJECTIVE: To develop and compare machine learning models based on CT morphology features, serum biomarkers, and basic physical conditions to predict esophageal variceal bleeding.

Authors

  • Haichen Zhao
    Department of Radiology, The Affiliated Hospital of Qingdao University, Qingdao, China.
  • Xiaoya Zhang
    Key Laboratory for Optoelectronic Technology and System of the Education Ministry of China, College of Optoelectronic Engineering, Chongqing University, Chongqing, China.
  • Baoxiang Huang
    Guangdong Medical University, Dongguan 523808, China.
  • Xiaojuan Shi
    Department of Radiology, The Affiliated Hospital of Qingdao University, Qingdao, China.
  • Longyang Xiao
    Department of Radiology, The Affiliated Hospital of Qingdao University, Qingdao, China.
  • Zhiming Li
    Department of Radiology, The Affiliated Hospital of Qingdao University, Qingdao, China. Electronic address: lizhiming@qdu.edu.cn.

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