CT-based AI framework leveraging multi-scale features for predicting pathological grade and Ki67 index in clear cell renal cell carcinoma: a multicenter study.

Abstract

Authors

• Huancheng Yang
  Department of Radiology, The Sixth Affiliated Hospital of Sun Yat-sen University, Guangzhou, China.
• Yueyue Zhang
  Department of Radiology, The Second Affiliated Hospital of Soochow University, Suzhou, 215004, Jiangsu, China.
• Fan Li
  Department of Instrument Science and Engineering, School of SEIEE, Shanghai Jiao Tong University, Shanghai 200240, China.
• Weihao Liu
  Computer School, Hubei University of Arts and Science, Longzhong Road, Xiangyang, 441053, Hubei, China.
• Haoyang Zeng
  Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge, MA 02142, USA.
• Haoyuan Yuan
  Shantou University Medical College, Shantou University, Shantou, China.
• Zixi Ye
  Shantou University Medical College, Shantou University, Shantou, China.
• Zexin Huang
  Department of Radiology, Shenzhen Luohu District Traditional Chinese Medicine Hospital (Luohu Hospital Group), Shenzhen, China.
• Yangguang Yuan
  Department of Radiology, The Third Affiliated Hospital of Shenzhen University (Luohu Hospital Group), Shenzhen, China.
• Ye Xiang
  Faculty of Information Technology, Beijing University of Technology, Beijing 100124, China.
• Kai Wu
• Hanlin Liu
  Department of Ocean and Mechanical Engineering, Florida Atlantic University, Boca Raton, FL, United States of America.

Keywords

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