Improving the Prognostic Evaluation Precision of Hospital Outcomes for Heart Failure Using Admission Notes and Clinical Tabular Data: Multimodal Deep Learning Model.

Abstract

Authors

• Zhenyue Gao
  School of Automation and Electrical Engineering, University of Science and Technology Beijing, Beijing 100083, P. R. China.
• Xiaoli Liu
  Neurology Department, Zhejiang Hospital, Zhejiang 310013, China.
• Yu Kang
  College of Pharmaceutical Sciences, Zhejiang University , Hangzhou, Zhejiang 310058, P. R. China.
• Pan Hu
  Department of Anesthesiology, The 920 Hospital of Joint Logistic Support Force of Chinese PLA, Kunming Yunnan, CHINA.
• Xiu Zhang
• Wei Yan
  State & Local Joint Engineering Research Center of Green Pesticide Invention and Application, College of Plant Protection, Nanjing Agricultural University, Nanjing 210095, China. Electronic address: yanwei@njau.edu.cn.
• Muyang Yan
  Center for Artificial Intelligence in Medicine, The General Hospital of People's Liberation Army, Beijing, China.
• Pengming Yu
  Department of Cardiology, West China Hospital, Sichuan University, Chengdu, China.
• Qing Zhang
  Department of Respiratory Medicine, Affiliated Zhongshan Hospital of Dalian University, Dalian, China.
• Wendong Xiao
  School of Automation and Electrical Engineering, University of Science and Technology Beijing, Beijing 100083, China. wdxiao@ustb.edu.cn.
• Zhengbo Zhang
  Center for Artificial Intelligence in Medicine, Medical Innovation Research Department, PLA General Hospital, 100853, Beijing, China. Electronic address: zhengbozhang@126.com.

Keywords

External Resources