A novel deep learning prognostic system improves survival predictions for stage III non-small cell lung cancer.

Journal: Cancer medicine
Published Date: May 2, 2022

Abstract

BACKGROUND: Accurate prognostic prediction plays a crucial role in the clinical setting. However, the TNM staging system fails to provide satisfactory individual survival prediction for stage III non-small cell lung cancer (NSCLC). The performance of the deep learning network for survival prediction in stage III NSCLC has not been explored.

Authors

  • Linlin Yang
    Cheeloo College of Medicine, Shandong University, Jinan, China.
  • Xinyu Fan
    Cheeloo College of Medicine, Shandong University, Jinan, China.
  • Wenru Qin
    Department of Radiation Oncology, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Science, Jinan, China.
  • Yiyue Xu
    Department of Radiation Oncology, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan 250117, China.
  • Bing Zou
    Department of Radiation Oncology, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Science, Jinan, China.
  • Bingjie Fan
    Department of Radiation Oncology, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Science, Jinan, China.
  • Shijiang Wang
    Department of Radiation Oncology, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Science, Jinan, China.
  • Taotao Dong
    Department of Obstetrics and Gynecology Qilu Hospital Cheeloo College of Medicine Shandong University Jinan Shandong China.
  • Linlin Wang
    Guangdong-Hong Kong-Macao Greater Bay Area Artificial Intelligence Application Technology Research Institute, Shenzhen Polytechnic University, Shenzhen, China.

Keywords

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