Artificial intelligence-driven multiomics predictive model for abdominal aortic aneurysm subtypes to identify heterogeneous immune cell infiltration and predict disease progression.

Abstract

Authors

• Lin Zhang
  Laboratory of Molecular Translational Medicine, Centre for Translational Medicine, Key Laboratory of Birth Defects and Related Diseases of Women and Children, Ministry of Education, Clinical Research Center for Birth Defects of Sichuan Province, West China Second Hospital, Sichuan University, Chengdu, Sichuan, 610041, China. Electronic address: zhanglin@scu.edu.cn.
• Han Yang
  Department of Biomedical Engineering, School of Medicine, Tsinghua University, Beijing, China.
• Chenxing Zhou
  Department of Spine and Osteopathy Ward, The First Affiliated Hospital of Guangxi Medical University, Nanning, P.R. China.
• Yao Li
  Center of Robotics and Intelligent Machine, Chongqing Institute of Green and Intelligent Technology, Chinese Academy of Science, No. 266 Fangzhen Road, Beibei District, Chongqing, 400714, China.
• Zhen Long
  The First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, PR China.
• Que Li
  Department of Vascular Surgery Ward, The First Affiliated Hospital of Guangxi Medical University, No.6 of Shuangyong Road, Nanning, Guangxi, 530021, P. R. China.
• Jiangfeng Zhang
  Department of Vascular Surgery Ward, The First Affiliated Hospital of Guangxi Medical University, No.6 of Shuangyong Road, Nanning, Guangxi, 530021, P. R. China.
• Xiao Qin
  Worcester Polytechnic Institute, 100 Institute Rd, Worcester, MA, 01609, USA.

Keywords

External Resources