Deep learning-based multi-model prediction for disease-free survival status of patients with clear cell renal cell carcinoma after surgery: a multicenter cohort study.

Journal: International journal of surgery (London, England)
PMID: 38445478

Abstract

BACKGROUND: Although separate analysis of individual factor can somewhat improve the prognostic performance, integration of multimodal information into a single signature is necessary to stratify patients with clear cell renal cell carcinoma (ccRCC) for adjuvant therapy after surgery.

Authors

  • Siteng Chen
    Department of Urology, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
  • Feng Gao
    Department of Statistics, UCLA, Los Angeles, CA 90095, USA.
  • Tuanjie Guo
    Department of Urology, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine.
  • Liren Jiang
    Department of Pathology, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
  • Ning Zhang
    Institute of Nuclear Agricultural Sciences, Zhejiang University, Hangzhou, 310058, China.
  • Xiang Wang
    Department of Thoracic Surgery, The Second Xiangya Hospital of Central South University, Changsha, Hunan, China.
  • Junhua Zheng
    Department of Urology, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.

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