A Deep Learning Model for Identifying the Risk of Mesenteric Malperfusion in Acute Aortic Dissection Using Initial Diagnostic Data: Algorithm Development and Validation.

Abstract

Authors

• Zhechuan Jin
  Department of Hepatobiliary Surgery, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, 710061, Shaanxi, China.
• Jiale Dong
  School of Information Engineering, Zhengzhou University, Zhengzhou 450001, China.
• Chengxiang Li
  Department of Hepatobiliary and Pancreaticosplenic Surgery, Beijing Chaoyang Hospital, Capital Medical University, Beijing, China.
• Yi Jiang
  Institute of Genomic Medicine, Wenzhou Medical University, Wenzhou 325035, China.
• Jian Yang
  Drug Discovery and Development Research Group, College of Pharmacy and Nutrition, University of Saskatchewan, Saskatoon, SK, Canada.
• Lei Xu
  Key Laboratory of Biomedical Information Engineering of the Ministry of Education, Department of Biomedical Engineering, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, China.
• Ping Li
  Department of Gastroenterology, Beijing Ditan Hospital, Capital Medical University, Beijing, China.
• Zhun Xie
  School of Instrumentation and Optoelectronic Engineering, Beihang University, Beijing, China.
• Yulin Li
  Department of Physics, and Fujian Provincial Key Laboratory for Soft Functional Materials Research, Xiamen University, Xiamen 361005, China.
• Dongjin Wang
  Department of Cardiac Surgery, Nanjing Drum Tower Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Graduate School of Peking Union Medical College, Beijing, China.
• Zhili Ji
  Department of General Surgery, Beijing Luhe Hospital, Capital Medical University, Tongzhou Qu, China.

Keywords

External Resources