Pathomics-based machine learning models for predicting pathological complete response and prognosis in locally advanced rectal cancer patients post-neoadjuvant chemoradiotherapy: insights from two independent institutional studies.

Abstract

Authors

• Yiyi Zhang
  Guangxi Key Laboratory of Power System Optimization and Energy Technology, Guangxi University, Nanning 530004, China. yiyizhang@gxu.edu.cn.
• Ying Huang
  Department of Otolaryngology, Head and Neck Surgery, Affiliated Hospital of Southwest Medical University Luzhou, Sichuan, China.
• Meifang Xu
  Zhejiang University International Hospital, Hangzhou, Zhejiang Province 310000, China.
• Jiazheng Zhuang
  Department of Gastrointestinal Surgery, The Quanzhou First Hospital Affiliated of Fujian Medical University, Quanzhou, China.
• Zhibo Zhou
  School of Computer Science and Engineering, Beihang University, Beijing, China.
• Shaoqing Zheng
  Fujian Medical University, Fuzhou, China.
• Bingwang Zhu
  Department of Colorectal Surgery, The First Affiliated Hospital of Fujian Medical University, Fuzhou, China.
• Guoxian Guan
  Department of Colorectal Surgery, The First Affiliated Hospital of Fujian Medical University, Fuzhou, China. fjxhggx@163.com.
• Hong Chen
  Department of Nephrology, The Second Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, China.
• Xing Liu
  School of Food Science and Engineering, Hainan University 58 Renmin Avenue Haikou 570228 China zhangzeling@hainanu.edu.cn benchao312@hainanu.edu.cn xuhuan.hnu@foxmail.com qichen@hainanu.edu.cn sunzhichang11@163.com hmcao@hainanu.edu.cn.

Keywords

External Resources