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Morteza Zabihi
Morteza Zabihi
Harvard Medical School and Massachusetts General Hospital
Verified email at mgh.harvard.edu - Homepage
Title
Cited by
Cited by
Year
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
2012016
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
1782017
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
1432015
Automated patient-specific classification of long-term electroencephalography
S Kiranyaz, T Ince, M Zabihi, D Ince
Journal of biomedical informatics 49, 16-31, 2014
892014
Early Detection of Myocardial Infarction in Low-Quality Echocardiography
A Degerli, M Zabihi, S Kiranyaz, T Hamid, R Mazhar, R Hamila, ...
IEEE Access 9, 34442-34453, 2021
632021
Patient-Specific Seizure Detection Using Nonlinear Dynamics and Nullclines
M Zabihi, S Kiranyaz, V Jäntti, T Lipping, M Gabbouj
IEEE journal of biomedical and health informatics 24 (2), 543-555, 2019
532019
Sepsis Prediction in Intensive Care Unit Using Ensemble of XGboost Models
M Zabihi, S Kiranyaz, M Gabbouj
2019 Computing in Cardiology (CinC), Page 1-Page 4, 2019
452019
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
432020
Left Ventricular Wall Motion Estimation by Active Polynomials for Acute Myocardial Infarction Detection
S Kiranyaz, A Degerli, T Hamid, R Mazhar, REF Ahmed, R Abouhasera, ...
IEEE Access 8, 210301-210317, 2020
312020
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
282019
Patient-specific epileptic seizure detection in long-term EEG recording in paediatric patients with intractable seizures
M Zabihi, S Kiranyaz, T Ince, M Gabbouj
IET Digital Library, 2013
262013
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
192019
Real-time PCG Anomaly Detection by Adaptive 1D Convolutional Neural Networks
S Kiranyaz, M Zabihi, AB Rad, A Tahir, T Ince, R Hamila, M Gabbouj
arXiv preprint arXiv:1902.07238, 2019
112019
Sepsis prediction in intensive care unit using ensemble of XGboost models. in 2019 Computing in Cardiology (CinC)
M Zabihi, S Kiranyaz, M Gabbouj
IEEE, Page–1, 2019
112019
ECG rhythm analysis during manual chest compressions using an artefact removal filter and random forest classifiers
I Isasi, AB Rad, U Irusta, M Zabihi, E Aramendi, T Eftestøl, ...
2018 Computing in Cardiology Conference (CinC) 45, 1-4, 2018
92018
Learned vs. hand-designed features for ECG beat classification: A comprehensive study
T Ince, M Zabihi, S Kiranyaz, M Gabbouj
EMBEC & NBC 2017: Joint Conference of the European Medical and Biological …, 2018
92018
Automatic sleep arousal detection using state distance analysis in phase space
M Zabihi, AB Rad, S Särkkä, S Kiranyaz, AK Katsaggelos, M Gabbouj
2018 Computing in Cardiology Conference (CinC) 45, 1-4, 2018
82018
Automated Polysomnography Analysis for Detection of Non-Apneic and Non-Hypopneic Arousals using Feature Engineering and a Bidirectional LSTM Network
AB Rad, M Zabihi, Z Zhao, M Gabbouj, AK Katsaggelos, S Särkkä
arXiv preprint arXiv:1909.02971, 2019
52019
Feasibility of video/audio monitoring in the analysis of motion and treatment effects on night-time seizures – interventional study
P Ojanen, M Zabihi, A Knight, R Roivanen, S Lamusuo, J Peltola
Epilepsy Research, 2022
42022
1D convolutional neural network models for sleep arousal detection. arXiv
M Zabihi, AB Rad, S Kiranyaz, S Särkkä, M Gabbouj
arXiv preprint arXiv:1903.01552, 2019
42019
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