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Automated quantification of atrial fibrillation complexity by probabilistic electrogram analysis and fibrillation wave reconstruction.

, , , , , , and . EMBC, page 6357-6360. IEEE, (2012)

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Tracking of Atrial Fibrillation Drivers Based on Propagation Patterns: An In-Silico Study., , , , , , and . CinC, page 1-4. IEEE, (2022)Principal Component Analysis of Body Surface Potential Mapping in Atrial Fibrillation Patients Suggests Additional ECG Lead Locations., , , , and . CinC, page 893-896. www.cinc.org, (2014)Noninvasive Characterization of Short- and Long-Term Recurrence of Atrial Signals During Persistent Atrial Fibrillation., , , , , , , , and . CinC, www.cinc.org, (2017)Spurious Rotor Detection During Atrial Fibrillation: Phase Singularities in Fact Reflect Blurred Conduction Block., , , , , and . CinC, www.cinc.org, (2017)State Space Embedding of Atrial Electrograms to Detect Repetitive Conduction Patterns During Atrial Fibrillation., , , , and . EMBC, page 508-511. IEEE, (2021)Noninvasive Recurrence Quantification Analysis Predicts Atrial Fibrillation Recurrence in Persistent Patients Undergoing Electrical Cardioversion., , , , , , , and . CinC, www.cinc.org, (2016)Fibrosis Reduces the Coincidence of Repetitive Activation Patterns between the Coronary Sinus and Atrial Regions in Simulated Atrial Fibrillation., , , , , , , , and . CinC, page 1-4. IEEE, (2022)Beat-to-beat P-wave Variability Increases From Paroxysmal to Persistent Atrial Fibrillation., , , , , , and . CinC, page 1-4. IEEE, (2020)Sparse Gene Regulatory Network Identification., and . KDECB, volume 4366 of Lecture Notes in Computer Science, page 171-182. Springer, (2006)Towards Standardization of Non-invasive Atrial Fibrillation Substrate Complexity Quantification: Effect of Choice of ECG-leads and Complexity Measure on Prediction of Pharmacological Cardioversion., , , and . CinC, page 879-882. www.cinc.org, (2013)