Electrocardiogram Classification Using Long Short-Term Memory Networks

[1]  Jeffrey M. Hausdorff,et al.  Physionet: Components of a New Research Resource for Complex Physiologic Signals". Circu-lation Vol , 2000 .

[2]  Nazife Baykal,et al.  A window-based time series feature extraction method , 2017, Comput. Biol. Medicine.

[3]  Sandeep Raj,et al.  Cardiac arrhythmia beat classification using DOST and PSO tuned SVM , 2016, Comput. Methods Programs Biomed..

[4]  Pierre Alliez,et al.  Convolutional Neural Networks for Large-Scale Remote-Sensing Image Classification , 2017, IEEE Transactions on Geoscience and Remote Sensing.

[5]  Michael S. Bernstein,et al.  ImageNet Large Scale Visual Recognition Challenge , 2014, International Journal of Computer Vision.

[6]  Byunghan Lee,et al.  Deep learning in bioinformatics , 2016, Briefings Bioinform..

[7]  Yoshua. Bengio,et al.  Learning Deep Architectures for AI , 2007, Found. Trends Mach. Learn..

[8]  U. Rajendra Acharya,et al.  A deep convolutional neural network model to classify heartbeats , 2017, Comput. Biol. Medicine.

[9]  Andrew W. Senior,et al.  Long short-term memory recurrent neural network architectures for large scale acoustic modeling , 2014, INTERSPEECH.

[10]  Peng Lu,et al.  Research on Improved Depth Belief Network-Based Prediction of Cardiovascular Diseases , 2018, Journal of healthcare engineering.

[11]  Wei Li,et al.  Local Deep Field for Electrocardiogram Beat Classification , 2018, IEEE Sensors Journal.

[12]  Heeyoung Kim,et al.  Detection of PVC by using a wavelet-based statistical ECG monitoring procedure , 2017, Biomed. Signal Process. Control..