Dr.-Ing. Giorgio Luongo

  • Alumnus

Auszeichnung

2022

Klee-Preis für Giorgio Luongo
Die Deutsche Gesellschaft für Biomedizinische Technik (DGBMT) vergibt jährlich den Klee-Preis an Wissenschaftler*innen für praxisnahe Entwicklungen im Bereich der Medizintechnik. Giorgio Luongo wurde für seine Dissertation "Non-Invasive Atrial Arrhythmia Diagnosis Using the 12-Lead ECG: Machine Learning Leveraging in-silico and Clinical Signals” am IBT mit dem 3. Platz ausgezeichnet.
[Pressemeldung] [Dissertation]

Veröffentlichungen


  Alle Veröffentlichungen, sortiert nach Jahren

          2022  2021  2020  2019  [Alle]


Ausgewählte Veröffentlichungen

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
  PDF        
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
  PDF    
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
  PDF        
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
  PDF      
D. Nairn, M. Eichenlaub, B. Müller-Edenborn, H. Lehrmann, C. Nagel, L. Azzolin, G. Luongo, R. Figueras Ventura, B. Rubio Forcada, A. Colomer, T. Arentz, O. Dössel, A. Loewe, and A. Jadidi.
LGE-MRI for diagnosis of left atrial cardiomyopathy as identified in high-definition endocardial voltage and conduction velocity mapping.
In medRxiv, 2022
  PDF    
D. Nairn, M. Eichenlaub, H. Lehrmann, B. Müller-Edenborn, J. Chen, T. Huang, C. Nagel, J. Sánchez, G. Luongo, T. Arentz, O. Dössel, A. Jadidi, and A. Loewe.
Spatial Correlation of Left Atrial Low Voltage Substrate in Sinus Rhythm versus Atrial Fibrillation: Identifying the Pathological Substrate Irrespective of the Rhythm.
2022
  PDF    
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) , 2021
  PDF        
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
  PDF        
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
  PDF      
O. Dössel, G. Luongo, C. Nagel, and A. Loewe.
Computer Modeling of the Heart for ECG Interpretation—A Review.
In Hearts, vol. 2(3) , pp. 350-368, 2021
  PDF        

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
  PDF    
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
  PDF    
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
  PDF        
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
  PDF      
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 Computing in Cardiology, 2020
  PDF      
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
  PDF  
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
  PDF  
M. Vila, M. W. Rivolta, G. Luongo, A. Loewe, and R. Sassi.
Directed Network Mapping Hints the Ablation Strategy for Atrial Flutter: a Proof of Concept.
In 4th Atrial Signals Proceedings, pp. 16, 2021
  PDF  
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
  PDF      
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
  PDF