ECGNet: An Efficient Network for Detecting Premature Ventricular Complexes Based on ECG Images

Author:

Zhang Zeyang1ORCID,Zhang Ziheng2,Zou Cao3,Pei Zhongcai1ORCID,Yang Zheyuan2,Wu Jing4,Sun Shikun5,Gu Fei6ORCID

Affiliation:

1. School of Automation Science and Electrical Engineering, Beihang University, China

2. School of Computer Science and Technology, Soochow University, China

3. Department of Cardiology, The First Affiliated Hospital of Soochow University, China

4. School of Public Health, Medical College of Soochow University, China

5. Department of Cardiology, The First Affiliated Hospital of Soochow University, Suzhou, China

6. School of Computer Science and Technology, Soochow University, Suzhou, China

Funder

National Science Foundation of the Jiangsu Higher Education Institutions of China

Suzhou Planning Project of Science and Technology

Future Network Scientific Research Fund Project

Priority Academic Program Development of Jiangsu Higher Education Institutions

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Biomedical Engineering

Reference44 articles.

1. EfficientNet: Rethinking model scaling for convolutional neural networks;tan;Proc IEEE Int Conf Mach Learn,0

2. Pareto Distribution

3. Outcomes of catheter ablation of ventricular arrhythmia originating from the left ventricular summit: A multicenter study

4. Value of a posterior electrocardiographic lead for localization of ventricular outflow tract arrhythmias: The V$_{4}$/V$_{8}$ ratio;zhang;J Amer College Cardiol Clin Electrophysiol,2017

5. V 3 R/V 7 Index

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