Opportunities and Challenges of Deep Learning Methods for
Electrocardiogram Data: A Systematic Review

Opportunities and Challenges of Deep Learning Methods for Electrocardiogram Data: A Systematic Review

28 December 2019

Jimeng Sun

Papers citing "Opportunities and Challenges of Deep Learning Methods for Electrocardiogram Data: A Systematic Review"

7 / 7 papers shown

Title
Deep Neural Networks Generalization and Fine-Tuning for 12-lead ECG Classification A. Avetisyan Shahane Tigranyan A. Asatryan O. Mashkova Sergey Skorik V. Ananev Yury Markin LM&MA 27 5 0 19 May 2023
LightX3ECG: A Lightweight and eXplainable Deep Learning System for 3-lead Electrocardiogram Classification Khiem H. Le Hieu H. Pham Thao BT. Nguyen Tu Nguyen T. Thanh Cuong D. Do 18 34 0 25 Jul 2022
Decorrelative Network Architecture for Robust Electrocardiogram Classification Christopher Wiedeman Ge Wang OOD 13 2 0 19 Jul 2022
Robustness of convolutional neural networks to physiological ECG noise Jenny Venton P. Harris A. Sundar N. Smith P. Aston 39 26 0 02 Aug 2021
Self-supervised representation learning from 12-lead ECG data Temesgen Mehari Nils Strodthoff SSL 21 141 0 23 Mar 2021
Interpretable Deep Learning for Automatic Diagnosis of 12-lead Electrocardiogram Dongdong Zhang Xiaohui Yuan Ping Zhang 21 111 0 20 Oct 2020
HOLMES: Health OnLine Model Ensemble Serving for Deep Learning Models in Intensive Care Units linda Qiao Yanbo Xu Alind Khare Satria Priambada K. Maher Alaa Aljiffry Jimeng Sun Alexey Tumanov OOD 31 85 0 10 Aug 2020