Comparison of machine learning methods for Predicting 3-Year survival in elderly esophageal squamous cancer patients based on oxidative stress.

Journal: BMC cancer
PMID: 39574068

Abstract

BACKGROUND: Oxidative stress process plays a key role in aging and cancer; however, currently, there is paucity of machine-learning model studies investigating the relationship between oxidative stress and prognosis of elderly patients with esophageal squamous cancer (ESCC).

Authors

  • Jin-Biao Xie
    Department of Cardiothoracic Surgery, The Affiliated Hospital of Putian University, No.999 Dongzhen Road, Fujian, 351100, China. jinbiaoxie123@163.com.
  • Shi-Jie Huang
    Department of Cardiothoracic Surgery, The Affiliated Hospital of Putian University, No.999 Dongzhen Road, Fujian, 351100, China.
  • Tian-Bao Yang
    Department of Cardiothoracic Surgery, The Affiliated Hospital of Putian University, No.999 Dongzhen Road, Fujian, 351100, China.
  • Wu Wang
    College of Electrical Engineering and Automation, Fuzhou University, Fuzhou 350108, China.
  • Bo-Yang Chen
    Department of Cardiothoracic Surgery, The Affiliated Hospital of Putian University, No.999 Dongzhen Road, Fujian, 351100, China.
  • Lianyi Guo
    Department of Gastroenterology, The First Affiliated Hospital of Jinzhou Medical University, Jinzhou, 121001, China.

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