Combining convolutional neural network and distance distribution matrix for identification of congestive heart failure

• Main Authors: Li, Yaowei, Zhang, Yao, Zhao, Lina, Zhang, Yang, Liu, Chengyu, Zhang, Li, Zhang, Liuxin, Li, Zhensheng, Wang, Binhua, Ng, Eyk, Li, Jianqing, He, Zhiqiang
• Other Authors: School of Mechanical and Aerospace Engineering
• Format: Article
• Language: English
• Published: 2018
• Subjects: Congestive Heart Failure; Convolutional Neural Network; DRNTU::Engineering::Electrical and electronic engineering
• Online Access: https://hdl.handle.net/10356/88148; http://hdl.handle.net/10220/45646
• Institution: Nanyang Technological University

Congestive heart failure (CHF) is a serious pathophysiological condition with high morbidity and mortality, which is hard to predict and diagnose in early age. Artificial intelligence and deep learning combining with cardiac rhythms and physiological time series provide a potential to help in solvin...