Developing a CT radiomics-based model for assessing split renal function using machine learning.

Abstract

Authors

• Yihua Zhan
  State Key Laboratory of Plant Physiology and Biochemistry, College of Life Sciences, Zhejiang University, Hangzhou, 310058, China.
• Junjiong Zheng
  The Sun Yat-Sen Memorial Hospital of Sun Yat-Sen University, Guangzhou, China.
• Xutao Chen
  The Sun Yat-Sen Memorial Hospital of Sun Yat-Sen University, Guangzhou, China.
• Yushu Chen
  The Eighth Affiliated Hospital of Sun Yat-Sen University, Shenzhen, China.
• Chao Fang
  Department of Electrical Engineering and Computer Science, University of Missouri, Columbia, Missouri.
• Cong Lai
  Department of Urology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China.
• Mingzhou Dai
  The Sun Yat-Sen Memorial Hospital of Sun Yat-Sen University, Guangzhou, China.
• Zhikai Wu
  Department of Urology, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, No. 107 Yanjiang West Road, Guangzhou, 510000, Guangdong, China.
• Han Wu
  Department of Thoracic Surgery, Ruijin Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, China.
• Taihui Yu
  Department of Radiology, Sun Yat-sen Memorial Hospital, Guangdong, Guangzhou, China.
• Jian Huang
  Center for Informational Biology, University of Electronic Science and Technology of China, No. 2006, Xiyuan Ave, West Hi-Tech Zone, Chengdu 611731, P. R. China.
• Hao Yu
  Shanghai Key Lab of Trustworthy Computing, East China Normal University, Shanghai, China.

Keywords

External Resources