Ali Bahrami Rad
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Classification of 12-lead ecgs: the physionet/computing in cardiology challenge 2020
EAP Alday, A Gu, AJ Shah, C Robichaux, AKI Wong, C Liu, F Liu, AB Rad, ...
Physiological measurement 41 (12), 124003, 2020
Heart sound anomaly and quality detection using ensemble of neural networks without segmentation
M Zabihi, AB Rad, S Kiranyaz, M Gabbouj, AK Katsaggelos
2016 computing in cardiology conference (CinC), 613-616, 2016
Detection of atrial fibrillation in ECG hand-held devices using a random forest classifier
M Zabihi, AB Rad, AK Katsaggelos, S Kiranyaz, S Narkilahti, M Gabbouj
2017 Computing in Cardiology (CinC), 1-4, 2017
Will two do? Varying dimensions in electrocardiography: the PhysioNet/Computing in Cardiology Challenge 2021
MA Reyna, N Sadr, EAP Alday, A Gu, AJ Shah, C Robichaux, AB Rad, ...
2021 Computing in Cardiology (CinC) 48, 1-4, 2021
Analysis of high-dimensional phase space via Poincaré section for patient-specific seizure detection
M Zabihi, S Kiranyaz, AB Rad, AK Katsaggelos, M Gabbouj, T Ince
IEEE Transactions on Neural Systems and Rehabilitation Engineering 24 (3 …, 2015
The CirCor DigiScope dataset: from murmur detection to murmur classification
J Oliveira, F Renna, PD Costa, M Nogueira, C Oliveira, C Ferreira, ...
IEEE journal of biomedical and health informatics 26 (6), 2524-2535, 2021
ECG-based classification of resuscitation cardiac rhythms for retrospective data analysis
AB Rad, T Eftestøl, K Engan, U Irusta, JT Kvaløy, J Kramer-Johansen, ...
IEEE Transactions on Biomedical Engineering 64 (10), 2411-2418, 2017
Classification of 12-lead ECGs: the PhysioNet
EA Perez Alday, A Gu, A Shah, C Robichaux, AKI Wong, C Liu, F Liu, ...
Computing in Cardiology challenge, 2020
Heart murmur detection from phonocardiogram recordings: The george b. moody physionet challenge 2022
MA Reyna, Y Kiarashi, A Elola, J Oliveira, F Renna, A Gu, EAP Alday, ...
2022 Computing in Cardiology (CinC) 498, 1-4, 2022
Predicting neurological recovery from coma after cardiac arrest: The George B. Moody PhysioNet Challenge 2023
MA Reyna, E Amorim, R Sameni, J Weigle, A Elola, AB Rad, S Seyedi, ...
2023 Computing in Cardiology (CinC) 50, 1-4, 2023
Machine learning methods for neonatal mortality and morbidity classification
J Jaskari, J Myllärinen, M Leskinen, AB Rad, J Hollmén, S Andersson, ...
Ieee Access 8, 123347-123358, 2020
Real-time phonocardiogram anomaly detection by adaptive 1D convolutional neural networks
S Kiranyaz, M Zabihi, AB Rad, T Ince, R Hamila, M Gabbouj
Neurocomputing 411, 291-301, 2020
Spectro-temporal ECG analysis for atrial fibrillation detection
Z Zhao, S Särkkä, AB Rad
2018 IEEE 28Th international workshop on machine learning for signal …, 2018
Automatic cardiac rhythm classification with concurrent manual chest compressions
I Isasi, U Irusta, AB Rad, E Aramendi, M Zabihi, T Eftestøl, ...
IEEE Access 7, 115147-115159, 2019
Issues in the automated classification of multilead ECGs using heterogeneous labels and populations
MA Reyna, N Sadr, EAP Alday, A Gu, AJ Shah, C Robichaux, AB Rad, ...
Physiological Measurement 43 (8), 084001, 2022
Will two do? varying dimensions in electrocardiography: The physionet/computing in cardiology challenge 2021. In 2021 Computing in Cardiology (CinC)
MA Reyna, N Sadr, EAP Alday, A Gu, AJ Shah, C Robichaux, AB Rad, ...
IEEE 48, 1-4, 2021
Classification and prediction of post-trauma outcomes related to PTSD using circadian rhythm changes measured via wrist-worn research watch in a large longitudinal cohort
AS Cakmak, EAP Alday, G Da Poian, AB Rad, TJ Metzler, TC Neylan, ...
IEEE journal of biomedical and health informatics 25 (8), 2866-2876, 2021
Kalman-based spectro-temporal ECG analysis using deep convolutional networks for atrial fibrillation detection
Z Zhao, S Särkkä, AB Rad
Journal of Signal Processing Systems 92, 621-636, 2020
Automatic cardiac rhythm interpretation during resuscitation
AB Rad, K Engan, AK Katsaggelos, JT Kvaløy, L Wik, J Kramer-Johansen, ...
Resuscitation 102, 44-50, 2016
1d convolutional neural network models for sleep arousal detection
M Zabihi, AB Rad, S Kiranyaz, S Särkkä, M Gabbouj
arXiv preprint arXiv:1903.01552, 2019
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