Machine Learning-based Nomograms for Predicting Clinical Stages of Initial Prostate Cancer: A Multicenter Retrospective Study.

Journal: Urology
Published Date:

Abstract

OBJECTIVE: To construct and externally validate machine learning-based nomograms for predicting progression stages of initial prostate cancer (PCa) using biomarkers and clinicopathologic features.

Authors

  • Luyao Chen
    School of International Chinese Language Education, Beijing Normal University, Beijing 100875, China.
  • Zhehong Fu
    Department of Computer Science, Columbia University, New York, New York, USA.
  • Qianxi Dong
    Jiangxi Provincial Key Laboratory of Urinary System Diseases, Department of Urology, The First Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang, Jiangxi, China.
  • Fuchun Zheng
    Department of Urology, The First Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang, Jiangxi, China.
  • Zhipeng Wang
    Department of Pharmacy, Changzheng Hospital, Second Military Medical University, Shanghai, 200003, PR China.
  • Sheng Li
    School of Data Science, University of Virginia, Charlottesville, VA, United States.
  • Xiangpeng Zhan
    Department of Urology, The First Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang, Jiangxi, China.
  • Wentao Dong
    School of Electrical and Automation Engineering, East China Jiaotong University, Nanchang, 330013, China.
  • Yanping Song
    School of Public Administration, Central South University, Changsha, Hunan, China.
  • Songhui Xu
    Department of Urology, The First Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang, Jiangxi, China.
  • Bin Fu
    Department of Orthopaedic Surgery, Changzhou Wujin People's Hospital, Changzhou 213100, China.
  • Situ Xiong
    Department of Urology, The First Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang, Jiangxi, China.