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Personalization of Atrial Fibrillation Antiarrhythmic Drug Treatments: a Population of Models Approach., , , , , , , , and . CinC, www.cinc.org, (2017)Non-invasive Detection of Reentrant Drivers during Atrial Fibrillation: a Clinical-Computational Study., , , , , , , , and . CinC, page 9-12. www.cinc.org, (2014)Solving Inaccuracies in Anatomical Models for Electrocardiographic Inverse Problem Resolution by Maximizing Reconstruction Quality., , , , , , , , and . IEEE Trans. Med. Imaging, 37 (3): 733-740 (2018)Phase singularity point tracking for the identification of typical and atypical flutter patients: A clinical-computational study., , , , , , , and . Comp. in Bio. and Med., (2019)Multiple Cardiac Disease Detection from Minimal-Lead ECG Combining Feedforward Neural Networks with a One-vs-Rest Approach., , , , and . CinC, page 1-4. IEEE, (2021)Arrhythmic3D: a fast automata-based tool to simulate and assess arrhythmia risk in 3D ventricular models., , , , , , , , and . CinC, page 1-4. IEEE, (2021)Evaluation of Inverse Problem with Slow-Conducting Channel in Scar Area in a Post-Infarction Model., , , , , , and . CinC, www.cinc.org, (2017)Accuracy of Inverse Solution Computation of Dominant Frequencies and Phases during Atrial Fibrillation., , , , , , , , , and . CinC, page 537-540. www.cinc.org, (2014)Noninvasive Identification of Atrial Fibrillation Drivers: Simulation and Patient Data Evaluation., , , , , , , and . CinC, www.cinc.org, (2016)Performance of Inverse Problem Regularization Methods for Driver Location during Atrial Fibrillation., , , , , , , , , and . CinC, www.cinc.org, (2016)