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Journal Articles (10)
G. Luongo, G. Vacanti, V. Nitzke, D. Nairn, C. Nagel, D. Kabiri, T. P. Almeida, D. C. Soriano, M. W. Rivolta, G. A. Ng, O. Dössel, A. Luik, R. Sassi, C. Schmitt, and A. Loewe.
Hybrid machine learning to localize atrial flutter substrates using the surface 12-lead electrocardiogram.
In EP Europace, vol. 24(7) , pp. 1186-1194, 2022
Hybrid machine learning to localize atrial flutter substrates using the surface 12-lead electrocardiogram.
In EP Europace, vol. 24(7) , pp. 1186-1194, 2022
G. Luongo, F. Rees, D. Nairn, M. W. Rivolta, O. Dössel, R. Sassi, C. Ahlgrim, L. Mayer, F.-J. Neumann, T. Arentz, A. Jadidi, A. Loewe, and B. Müller-Edenborn.
Machine Learning Using a Single-Lead ECG to Identify Patients With Atrial Fibrillation-Induced Heart Failure.
In Frontiers in Cardiovascular Medicine, vol. 9, 2022
Machine Learning Using a Single-Lead ECG to Identify Patients With Atrial Fibrillation-Induced Heart Failure.
In Frontiers in Cardiovascular Medicine, vol. 9, 2022
G. Luongo, S. Schuler, A. Luik, T. P. Almeida, D. C. Soriano, O. Dossel, and A. Loewe.
Non-Invasive Characterization of Atrial Flutter Mechanisms Using Recurrence Quantification Analysis on the ECG: A Computational Study.
In IEEE Transactions on Biomedical Engineering, vol. 68(3) , pp. 914-925, 2021
Non-Invasive Characterization of Atrial Flutter Mechanisms Using Recurrence Quantification Analysis on the ECG: A Computational Study.
In IEEE Transactions on Biomedical Engineering, vol. 68(3) , pp. 914-925, 2021
G. Luongo, L. Azzolin, S. Schuler, M. W. Rivolta, T. P. Almeida, J. P. Martínez, D. C. Soriano, A. Luik, B. Müller-Edenborn, A. Jadidi, O. Dössel, R. Sassi, P. Laguna, and A. Loewe.
Machine learning enables noninvasive prediction of atrial fibrillation driver location and acute pulmonary vein ablation success using the 12-lead ECG.
In Cardiovascular Digital Health Journal, vol. 2(2) , pp. 126-136, 2021
Machine learning enables noninvasive prediction of atrial fibrillation driver location and acute pulmonary vein ablation success using the 12-lead ECG.
In Cardiovascular Digital Health Journal, vol. 2(2) , pp. 126-136, 2021
D. Nairn, M. Eichenlaub, B. Müller-Edenborn, T. Huang, H. Lehrmann, C. Nagel, L. Azzolin, G. Luongo, R. M. Figueras Ventura, B. Rubio Forcada, A. Vallès Colomer, D. Westermann, T. Arentz, O. Dössel, A. Loewe, and A. Jadidi.
Differences in atrial substrate localization using late gadolinium enhancement-magnetic resonance imaging, electrogram voltage, and conduction velocity: a cohort study using a consistent anatomical reference frame in patients with persistent atrial fibrillation.
In Europace, vol. 25(9) , 2023
Differences in atrial substrate localization using late gadolinium enhancement-magnetic resonance imaging, electrogram voltage, and conduction velocity: a cohort study using a consistent anatomical reference frame in patients with persistent atrial fibrillation.
In Europace, vol. 25(9) , 2023
D. Nairn, M. Eichenlaub, H. Lehrmann, B. Müller‐Edenborn, J. Chen, T. Huang, C. Nagel, J. Sánchez, G. Luongo, D. Westermann, T. Arentz, O. Dössel, A. Jadidi, and A. Loewe.
Spatial correlation of left atrial low voltage substrate in sinus rhythm versus atrial fibrillation: The rhythm specificity of atrial low voltage substrate.
In Journal of Cardiovascular Electrophysiology, vol. 34(8) , pp. 1613-1621, 2023
Spatial correlation of left atrial low voltage substrate in sinus rhythm versus atrial fibrillation: The rhythm specificity of atrial low voltage substrate.
In Journal of Cardiovascular Electrophysiology, vol. 34(8) , pp. 1613-1621, 2023
C. Nagel, G. Luongo, L. Azzolin, S. Schuler, O. Dössel, and A. Loewe.
Non-Invasive and Quantitative Estimation of Left Atrial Fibrosis Based on P Waves of the 12-Lead ECG—A Large-Scale Computational Study Covering Anatomical Variability.
In Journal of Clinical Medicine, vol. 10(8) , pp. 1797, 2021
Non-Invasive and Quantitative Estimation of Left Atrial Fibrosis Based on P Waves of the 12-Lead ECG—A Large-Scale Computational Study Covering Anatomical Variability.
In Journal of Clinical Medicine, vol. 10(8) , pp. 1797, 2021
J. Sánchez, G. Luongo, M. Nothstein, L. A. Unger, J. Saiz, B. Trenor, A. Luik, O. Dössel, and A. Loewe.
Using Machine Learning to Characterize Atrial Fibrotic Substrate From Intracardiac Signals With a Hybrid in silico and in vivo Dataset.
In Frontiers in Physiology, vol. 12, pp. 699291, 2021
Using Machine Learning to Characterize Atrial Fibrotic Substrate From Intracardiac Signals With a Hybrid in silico and in vivo Dataset.
In Frontiers in Physiology, vol. 12, pp. 699291, 2021
M. Vila, M. W. Rivolta, G. Luongo, L. A. Unger, A. Luik, L. Gigli, F. Lombardi, A. Loewe, and R. Sassi.
Atrial Flutter Mechanism Detection Using Directed Network Mapping.
In Frontiers in Physiology, vol. 12, 2021
Atrial Flutter Mechanism Detection Using Directed Network Mapping.
In Frontiers in Physiology, vol. 12, 2021
Book Chapters (1)
A. Loewe, G. Luongo, and J. Sánchez.
Machine Learning for Clinical Electrophysiology.
In Innovative Treatment Strategies for Clinical Electrophysiology, Springer Nature Singapore, Singapore, pp. 93-109, 2022
Machine Learning for Clinical Electrophysiology.
In Innovative Treatment Strategies for Clinical Electrophysiology, Springer Nature Singapore, Singapore, pp. 93-109, 2022
Conference Contributions (10)
G. Luongo, S. Schuler, M. W. Rivolta, O. Dössel, R. Sassi, and A. Loewe.
Semi-Supervised vs. Supervised Learning for Discriminating Atrial Flutter Mechanisms Using the 12-lead ECG.
In Computing in Cardiology Conference (CinC), vol. 48, 2021
Semi-Supervised vs. Supervised Learning for Discriminating Atrial Flutter Mechanisms Using the 12-lead ECG.
In Computing in Cardiology Conference (CinC), vol. 48, 2021
G. Luongo, S. Schuler, M. W. Rivolta, O. Dössel, R. Sassi, and A. Loewe.
Automatic classification of 20 different types of atrial tachycardia using 12-lead ECG signals.
In EP Europace, vol. 22(Supplement_1) , 2020
Automatic classification of 20 different types of atrial tachycardia using 12-lead ECG signals.
In EP Europace, vol. 22(Supplement_1) , 2020
G. Luongo, S. Schuler, M. W. Rivolta, O. Dössel, R. Sassi, and A. Loewe.
Automatic ECG-based Discrimination of 20 Atrial Flutter Mechanisms: Influence of Atrial and Torso Geometries.
In 2020 Computing in Cardiology(9344051) , pp. 1-4, 2020
Automatic ECG-based Discrimination of 20 Atrial Flutter Mechanisms: Influence of Atrial and Torso Geometries.
In 2020 Computing in Cardiology(9344051) , pp. 1-4, 2020
G. Luongo, L. Azzolin, M. W. Rivolta, R. Sassi, J. P. Martinez, P. Laguna, O. Doessel, and A. Loewe.
Non-invasive identification of atrial fibrillation driver location using the 12-lead ECG: pulmonary vein rotors vs. other locations.
In EMBC 20, 2020
Non-invasive identification of atrial fibrillation driver location using the 12-lead ECG: pulmonary vein rotors vs. other locations.
In EMBC 20, 2020
G. Luongo, L. Azzolin, M. W. Rivolta, T. P. Almeida, J. P. Martinez, D. C. Soriano, O. Dössel, R. Sassi, P. Laguna, and A. Loewe.
Machine Learning to Find Areas of Rotors Sustaining Atrial Fibrillation From the ECG.
In Computing in Cardiology, 2020
Machine Learning to Find Areas of Rotors Sustaining Atrial Fibrillation From the ECG.
In Computing in Cardiology, 2020
G. Luongo, S. Schuler, O. Dössel, and A. Loewe.
12-Lead ECG Feature Identification to Discriminate Different Types of Atrial Flutter.
In 41 Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 2019
12-Lead ECG Feature Identification to Discriminate Different Types of Atrial Flutter.
In 41 Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 2019
G. Luongo, S. Schuler, T. P. Almeida, D. C. Soriano, O. Dössel, and A. Loewe.
Discrimination of Atrial Flutter on Simulated 12-Lead-ECG Signals by Applying Biosignal Processing.
In Gordon Research Conference - Cardiac Arrhythmia Mechanisms, 2019
Discrimination of Atrial Flutter on Simulated 12-Lead-ECG Signals by Applying Biosignal Processing.
In Gordon Research Conference - Cardiac Arrhythmia Mechanisms, 2019
L. Azzolin, G. Luongo, S. Rocher, J. Saiz, O. Doessel, and A. Loewe.
Influence of Gradient and Smoothness of Atrial Wall Thickness on Initiation and Maintenance of Atrial Fibrillation.
In Computing in Cardiology Conference (CinC), 2020
Influence of Gradient and Smoothness of Atrial Wall Thickness on Initiation and Maintenance of Atrial Fibrillation.
In Computing in Cardiology Conference (CinC), 2020
A. S. Bezerra, T. Yoneyama, D. C. Soriano, G. Luongo, X. Li, F. Ravelli, M. Mase, G. S. Chu, P. J. Stafford, F. S. Schlindwein, G. A. Ng, and T. P. Almeida.
Optimazing Atrial Electrogram Classification Based on Local Ablation Outcome in Human Atrial Fibrillation.
In Computing in Cardiology Conference (CinC), 2020
Optimazing Atrial Electrogram Classification Based on Local Ablation Outcome in Human Atrial Fibrillation.
In Computing in Cardiology Conference (CinC), 2020