基于机器学习的自相关的预后签名,用于个性化风险分层和膀癌治疗方法

Zhen Wang1, Dong-Ning Chen1, Xu-Yun Huang1

  • 1Department of Urology, Urology Research Institute, the First Affiliated Hospital, Fujian Medical University, Fuzhou 350005, China; Department of Urology, National Regional Medical Center, Binhai Campus of the First Affiliated Hospital, Fujian Medical University, Fuzhou 350212, China.

概括

这项研究引入了膀癌 (BCa) 的自相关预后特征 (ARPS). 该ARPS工具增强了BCa患者的风险分层和决策,改善了预后预测.