Constructing a neural network model based on tumor-infiltrating lymphocytes (TILs) to predict the survival of hepatocellular carcinoma patients.

Journal: PeerJ
PMID: 40292102

Abstract

BACKGROUND: Hepatocellular carcinoma (HCC) is the most common primary liver cancer worldwide, and early pathological diagnosis is crucial for formulating treatment plans. Despite the widespread attention to pathology in the treatment of HCC patients, a large amount of information contained in pathological images is often overlooked.

Authors

  • Wenqing Zhong
    Department of Hepatobiliary and Pancreatic Surgery, The Affiliated Hospital of Qingdao University, Qingdao, Shandong, China.
  • Ziyin Zhao
    Organ Transplantation Center, The Affiliated Hospital of Qingdao University, Qingdao, Shandong, China.
  • Xin Fang
    School of Information Science and Technology, University of Science and Technology of China, Hefei 230022, China.
  • Jingyi Sun
    Department of Hepatobiliary and Pancreatic Surgery, The Affiliated Hospital of Qingdao University, Qingdao, Shandong, China.
  • Yanbing Wei
    Department of Hepatobiliary and Pancreatic Surgery, The Affiliated Hospital of Qingdao University, Qingdao, Shandong, China.
  • Fengda Li
    Department of Neurosurgery, Changshu Hospital Affiliated to Soochow University, Changshu, China.
  • Bing Han
    Harbin University of Commerce, Harbin, China.
  • Cheng Jin
    Department of Pathology, Hangzhou Women's Hospital, Hangzhou, 310008, Zhejiang, China.

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