Multimodal data integration using machine learning to predict the risk of clear cell renal cancer metastasis: a retrospective multicentre study.

Journal: Abdominal radiology (New York)
PMID:

Abstract

PURPOSE: To develop and validate a predictive combined model for metastasis in patients with clear cell renal cell carcinoma (ccRCC) by integrating multimodal data.

Authors

  • YouChang Yang
    Department of Radiology, Qilu Hospital (Qingdao), Cheeloo College of Medicine, Shandong University, Qingdao, 266035, China.
  • Jiajia Wang
    Department of Obstetrics and Gynecology, The Affiliated Hospital of Youjiang Medical University for Nationalities, Baise, China.
  • QingGuo Ren
    Department of Radiology, Qilu Hospital (Qingdao), Cheeloo College of Medicine, Shandong University, Qingdao, 266035, China.
  • Rong Yu
    Department of Neurology, Jiulongpo District Peoples Hospital, Chongqing, 400050, China.
  • ZiYi Yuan
    Department of Radiology, Qilu Hospital of Shandong University, Jinan, China.
  • QingJun Jiang
    Department of Radiology, Qilu Hospital (Qingdao), Cheeloo College of Medicine, Shandong University, Qingdao, 266035, China.
  • Shuai Guan
    Department of Radiology, Qilu Hospital (Qingdao), Cheeloo College of Medicine, Shandong University, Qingdao, 266035, China.
  • Xiaoqiang Tang
    Radiology Department, the Affiliated Changzhou No. 2 People's Hospital of Nanjing Medical University, Changzhou 213164, Jiangsu, China.
  • TongTong Duan
    Department of Ultrasound, The Affiliated Changzhou No. 2 People's Hospital of Nanjing Medical University, Changzhou, China.
  • Xiangshui Meng
    Department of Radiology, Qilu Hospital (Qingdao), Cheeloo College of Medicine, Shandong University, Jinan, Shandong, China.