A robust myocardial infarction localization system based on multi-branch residual shrinkage network and active learning with clustering

Author:

He Ziyang,Yuan Shuaiying,Zhao Jianhui,Yuan Zhiyong,Chen Yufei

Funder

Science and Technology Program of Hubei Province

Publisher

Elsevier BV

Subject

Health Informatics,Signal Processing,Biomedical Engineering

Reference57 articles.

1. O-WCNN: an optimized integration of spatial and spectral feature map for arrhythmia classification;Jangra;Complex Intell. Syst.,2021

2. Myocardial infarction classification with multi-lead ECG using hidden Markov models and Gaussian mixture models;Chang;Appl. Soft Comput.,2012

3. Third universal definition of myocardial infarction;Bax;J. Am. Coll. Cardiol.,2012

4. A new pattern recognition method for detection and localization of myocardial infarction using T-wave integral and total integral as extracted features from one cycle of ECG signal;Safdarian;J. Biomed. Sci. Eng.,2014

5. Automated analysis of ECG waveforms with atypical QRS complex morphologies;Tafreshi;Biomed. Signal Process. Control,2014

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