Construction of a combined prognostic model for pancreatic ductal adenocarcinoma based on deep learning and digital pathology images.

Journal: BMC gastroenterology
PMID: 39482576

Abstract

BACKGROUND: Deep learning has made significant advancements in the field of digital pathology, and the integration of multiple models has further improved accuracy. In this study, we aimed to construct a combined prognostic model using deep learning-extracted features from digital pathology images of pancreatic ductal adenocarcinoma (PDAC) alongside clinical predictive indicators and to explore its prognostic value.

Authors

  • Kaixin Hu
    Jiaxing University Master Degree Cultivation Base, Zhejiang Chinese Medical University, Jiaxing, Zhejiang, China.
  • Chenyang Bian
    Jiaxing University Master Degree Cultivation Base, Zhejiang Chinese Medical University, Jiaxing, Zhejiang, China.
  • Jiayin Yu
    Department of Hepatobiliary and Pancreatic Surgery, First Hospital of Jiaxing, Affiliated Hospital of Jiaxing University, Jiaxing, Zhejiang, China.
  • Dawei Jiang
    School of Biology and Biological Engineering, South China University of Technology, Guangzhou 510006, China.
  • Zhangjun Chen
    Jiaxing University Master Degree Cultivation Base, Zhejiang Chinese Medical University, Jiaxing, Zhejiang, China.
  • Fengqing Zhao
    Department of Hepatobiliary and Pancreatic Surgery, First Hospital of Jiaxing, Affiliated Hospital of Jiaxing University, Jiaxing, Zhejiang, China.
  • Huangbao Li
    Jiaxing University Master Degree Cultivation Base, Zhejiang Chinese Medical University, Jiaxing, Zhejiang, China. lhb641834@163.com.

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