| Reaction-diffusion informed approach to determine myocardial ischemia using stochastic in-silico ECGs and CNNs S Loeffler, J Starobin Computers in Biology and Medicine 136, 104635, 2021 | 6 | 2021 |
| Analytical Approach to Screen Semiconducting MOFs Using Bloch Mode Analysis and Spectroscopic Measurements H Rathnayake, S Saha, S Dawood, S Loeffler, J Starobin The Journal of Physical Chemistry Letters 12 (2), 884-891, 2021 | 6 | 2021 |
| Evaluation of severity of cardiac ischemia using in Silico ECG computed from 2D reaction diffusion model SE Loeffler, JM Starobin 2020 Computing in Cardiology, 1-4, 2020 | 2 | 2020 |
| Primer on Machine Learning in Electrophysiology SE Loeffler, N Trayanova Arrhythmia & Electrophysiology Review 12, 2023 | 1 | 2023 |
| Assessing the arrhythmogenic propensity of fibrotic substrate using digital twins to inform a mechanisms-based atrial fibrillation ablation strategy K Sakata, RP Bradley, A Prakosa, CAP Yamamoto, SY Ali, S Loeffler, ... Nature Cardiovascular Research, 1-12, 2024 | | 2024 |
| Predicting atrial fibrillation ablation success: a novel approach using pre-procedure sinus rhythm ecg and deep learning Y Mohsen, I Vatsaraj, S Loeffler, M Horlitz, F Stoeckigt, N Trayanova Europace 26 (Supplement_1), euae102. 021, 2024 | | 2024 |
| PO-02-054 EARLY DETECTION OF ATRIAL FUNCTIONAL MITRAL REGURGITATION IN ATRIAL FIBRILLATION PATIENTS USING ECG AND DEEP LEARNING Y Mohsen, I Vatsaraj, SE Loeffler, D Rottlaender, M Horlitz, F Stoeckigt, ... Heart Rhythm 21 (5), S280-S281, 2024 | | 2024 |
| PO-02-151 THE LESION OF PULMONARY VEIN ISOLATION PLAYS AN IMPORTANT ROLE IN ELIMINATING ROTOR SUBSTRATES: A STUDY USING PERSONALIZED LGE-MRI-BASED DIGITAL TWINS K Sakata, CYA Pinto, SY Ali, SE Loeffler, BM Tice, R Bradley, A Prakosa, ... Heart Rhythm 21 (5), S250, 2024 | | 2024 |
| MP-483492-009 REVEALING THE ATRIAL SUBSTRATE: A MULTIMODAL DEEP LEARNING APPROACH TO PREDICT THE ATRIAL SUBSTRATE USING 12-LEAD ECG ANALYSIS I Vatsaraj, Y Mohsen, SE Loeffler, M Horlitz, F Stoeckigt, NA Trayanova Heart Rhythm 21 (5), S64-S65, 2024 | | 2024 |
| PO-05-027 DETERMINING REENTRANT DRIVERS USING GRAPH NEURAL NETWORKS BASED ON LATE GADOLINIUM ENHANCEMENT MAGNETIC RESONANCE IMAGING SE Loeffler, Y Lal, A Yee, CYA Pinto, SY Ali, K Sakata, A Prakosa, ... Heart Rhythm 21 (5), S563, 2024 | | 2024 |
| PO-04-144 ABLATION LESIONS THEMSELVES CAN LEAD TO ATRIAL FIBRILLATION (AF) RECURRENCE: A STUDY EMPLOYING PERSONALIZED DIGITAL TWINS (DTS) DERIVED FROM LATE GADOLINIUM … CYA Pinto, K Sakata, SY Ali, SE Loeffler, A Prakosa, EG Kholmovski, ... Heart Rhythm 21 (5), S443, 2024 | | 2024 |
| A Simulation Study on the Inducibility of Atrial Fibrillation Drivers From Intra-Atrial Electrode Catheters Using Personalized Computational Models Based on LGE-MRI K Sakata, C Yamamoto Alves Pinto, SY Ali, S Loeffler, B Tice, RP Bradley, ... Circulation 148 (Suppl_1), A18514-A18514, 2023 | | 2023 |
| DETECTION OF MYOCARDIAL SCAR AMONG CARDIAC SARCOIDOSIS PATIENTS ON CMR IMAGING USING DEEP LEARNING ON ECG SIGNALS I Vatsaraj, S Loeffler, EG Kholmovski, J Chrispin, NA Trayanova Cardiovascular Digital Health Journal 4 (5), S2-S3, 2023 | | 2023 |
| PO-01-204 AN ARTIFICIAL INTELLIGENCE (AI)-ASSISTED END-TO-END COMPUTATIONAL PLATFORM FOR PREDICTION OF EXTRA-PULMONARY VEIN (EXTRA-PVI) ABLATION TARGETS IN ATRIAL FIBRILLATION … SY Ali, S Loeffler, CYA Pinto, A Lefebvre, R Bradley, K Sakata, A Prakosa, ... Heart Rhythm 20 (5), S189-S190, 2023 | | 2023 |
| PO-01-151 DEGREE OF FIBROSIS REMODELING ALTERS ATRIAL FIBRILLATION INDUCIBILITY CYA Pinto, R Bradley, SY Ali, A Prakosa, S Loeffler, K Sakata, ... Heart Rhythm 20 (5), S146-S147, 2023 | | 2023 |
| PO-02-100 ESTABLISHING A NON-EXCESSIVE ABLATION STRATEGY WITH THE USE OF PERSONALIZED ATRIAL COMPUTATIONAL MODELING K Sakata, R Bradley, CA Yamamoto, SY Ali, S Loeffler, A Prakosa, ... Heart Rhythm 20 (5), S349-S350, 2023 | | 2023 |
| Reentrant Drivers Are Distinguished From Passive Rotors by Sequential Computer Simulation of Ablation Using Personalized Non-Paroxysmal Atrial Fibrillation Heart Models Based … K Sakata, R Bradley, SY Ali, C Yamamoto Alves Pinto, S Loeffler, ... Circulation 146 (Suppl_1), A12792-A12792, 2022 | | 2022 |
| In Silico Electrocardiogram from Simplistic Geometric and Reaction Diffusion Model for Detection of Cardiac Ventricular Abnormalities Through Machine Learning … SE Loeffler The University of North Carolina at Greensboro, 2021 | | 2021 |
Natalia TrayanovaJohns Hopkins UniversityVerified email at jhu.edu
