Survival analysis of clear cell renal cell carcinoma based on radiomics and deep learning features from CT images.

Journal: Medicine
PMID:

Abstract

PURPOSE: To create a nomogram for accurate prognosis of patients with clear cell renal cell carcinoma (ccRCC) based on computed tomography images.

Authors

  • Zhennan Lu
    Department of Equipment, Affiliated Hospital of Nanjing University of Chinese Medicine (Jiangsu Province Hospital of Chinese Medicine), Nanjing, Jiangsu, China.
  • Sijia Wu
    School of Life Sciences and Technology, Xidian University, Xi'an 710126, China.
  • Dan Ni
    Affiliated Drum Tower Hospital, Medical School of Nanjing University, Nanjing, Jiangsu, China.
  • Meng Zhou
    College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, 150081, People's Republic of China. biofomeng@hotmail.com.
  • Tao Wang
    Department of Urology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
  • Xiaobo Zhou
    Department of Diagnostic Radiology, Wake Forest Medical School, Winston-Salem, NC 27103, USA. Electronic address: xizhou@wakehealth.edu.
  • Liyu Huang
    School of Life Science and Technology, Xidian University, Xi'an, 710071, Shaanxi, People's Republic of China. huangly@mail.xidian.edu.cn.
  • Yu Yan
    School of Preclinical Medicine, Guangxi Medical University, No. 22, Shuangyong Road, Nanning, Guangxi 530021, China.