A multimodal deep-learning model based on multichannel CT radiomics for predicting pathological grade of bladder cancer.

Journal: Abdominal radiology (New York)
Published Date: Dec 18, 2024

Abstract

OBJECTIVE: To construct a predictive model using deep-learning radiomics and clinical risk factors for assessing the preoperative histopathological grade of bladder cancer according to computed tomography (CT) images.

Authors

  • Ting Zhao
    Department of Neurology, Zhengzhou University People's Hospital, Henan Provincial People's Hospital, Henan Province, China.
  • Jian He
    School of Software Engineering, Beijing University of Technology, Beijing, China. Electronic address: jianhee@bjut.edu.cn.
  • Licui Zhang
    Department of Radiology, The Affiliated Hospital of Guizhou Medical University, Guizhou, China.
  • Hongyang Li
    Department of Computational Medicine and Bioinformatics, University of Michigan, 100 Washtenaw Avenue, Ann Arbor, MI, 48109, USA. hyangl@umich.edu.
  • Qinghong Duan
    Department of Radiology, The Affiliated Hospital of Guizhou Medical University, Guiyang, Guizhou Province, China.

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