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Eedara Prabhakararao
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Year
Myocardial infarction severity stages classification from ECG signals using attentional recurrent neural network
E Prabhakararao, S Dandapat
IEEE Sensors Journal 20 (15), 8711-8720, 2020
552020
B-Scan attentive CNN for the classification of retinal optical coherence tomography volumes
V Das, E Prabhakararao, S Dandapat, PK Bora
IEEE Signal Processing Letters 27, 1025-1029, 2020
332020
A weighted SVM based approach for automatic detection of posterior myocardial infarction using VCG signals
E Prabhakararao, S Dandapat
2019 national conference on communications (NCC), 1-6, 2019
242019
Multi-scale convolutional neural network ensemble for multi-class arrhythmia classification
E Prabhakararao, S Dandapat
IEEE Journal of Biomedical and Health Informatics 26 (8), 3802-3812, 2021
212021
On the use of variational mode decomposition for removal of baseline wander in ECG signals
E Prabhakararao, MS Manikandan
2016 Twenty Second National Conference on Communication (NCC), 1-6, 2016
212016
Automated detection of posterior myocardial infarction from VCG signals using stationary wavelet transform based features
E Prabhakararao, S Dandapat
IEEE Sensors Letters 4 (6), 1-4, 2020
192020
Attentive RNN-based network to fuse 12-lead ECG and clinical features for improved myocardial infarction diagnosis
E Prabhakararao, S Dandapat
IEEE Signal Processing Letters 27, 2029-2033, 2020
132020
Efficient and robust ventricular tachycardia and fibrillation detection method for wearable cardiac health monitoring devices
E Prabhakararao, MS Manikandan
Healthcare technology letters 3 (3), 239-246, 2016
122016
Atrial fibrillation burden estimation using multi-task deep convolutional neural network
E Prabhakararao, S Dandapat
IEEE Journal of Biomedical and Health Informatics 26 (12), 5992-6002, 2022
72022
Automatic quality estimation of 12-lead ECG for remote healthcare monitoring systems
E Prabhakararao, S Dandapat
2018 IEEE-EMBS Conference on Biomedical Engineering and Sciences (IECBES …, 2018
62018
Multiscale convolutional neural network for detecting paroxysmal atrial fibrillation from single lead ECG signals
E Prabhakararao, S Dandapat
2020 IEEE Applied Signal Processing Conference (ASPCON), 339-343, 2020
42020
Detection of life-threatening arrhythmias using random noise and zerocrossing information
E Prabhakararao, MS Manikandan
2016 International Conference on Wireless Communications, Signal Processing …, 2016
32016
Congestive Heart Failure Detection From ECG Signals Using Deep Residual Neural Network
E Prabhakararao, S Dandapat
IEEE Transactions on Systems, Man, and Cybernetics: Systems 53 (5), 3008-3018, 2022
12022
Multi-Label ECG Classification using Temporal Convolutional Neural Network
E Prabhakararao, S Dandapt
arXiv preprint arXiv:2306.03844, 2023
2023
Automated Diagnosis of Cardiac Disorders from Electrocardiogram Signals using Deep Learning
E Prabhakararao
Guwahati, 2023
2023
Biomedical Signal Processing Wavelet Based Waveform Distortion Measures for Assessment of Denoised EEG Quality With Reference to Noise-Free EEG Signal …
S Mukherjee, C Gonzalez-Gomez, L Danglot, T Lagache, JC Olivo-Marin, ...
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