Multi-machine learning model based on radiomics features to predict prognosis of muscle-invasive bladder cancer.

Journal: BMC cancer
Published Date: Jul 1, 2025

Abstract

OBJECTIVE: This study aims to construct a survival prognosis prediction model for muscle-invasive bladder cancer based on CT imaging features.

Authors

  • Bin Wang
    State Key Laboratory of Soil Erosion and Dryland Farming on the Loess Plateau, Northwest A&F University, Yangling 712100, China; New South Wales Department of Primary Industries, Wagga Wagga Agricultural Institute, Wagga Wagga 2650, Australia. Electronic address: bin.a.wang@dpi.nsw.gov.au.
  • Zijian Gong
    The Second Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang, China.
  • Peide Su
    The Second Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang, China.
  • Guanghao Zhen
    The Second Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang, China.
  • Tao Zeng
    Department of Urology, Second Affiliated Hospital of Nanchang University, Nanchang, China.
  • Yinquan Ye
    Department of Radiology, The Second Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang, Jiangxi, 330006, China.

Keywords

No keywords available for this article.

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