| Atrial fibrillation: Insights from animal models, computational modeling, and clinical studies C Yamamoto, NA Trayanova EBioMedicine 85, 2022 | 9 | 2022 |
| Lassnet: A four steps deep neural network for left atrial segmentation and scar quantification AL Lefebvre, CAP Yamamoto, JK Shade, RP Bradley, RA Yu, RL Ali, ... Challenge on Left Atrial and Scar Quantification and Segmentation, 1-15, 2022 | 5 | 2022 |
| High-resolution volumetric imaging constrains compartmental models to explore synaptic integration and temporal processing by cochlear nucleus globular bushy cells GA Spirou, M Kersting, S Carr, B Razzaq, CYA Pinto, M Dawson, ... Elife 12, e83393, 2023 | 2 | 2023 |
| Po-01-210 stroke risk is identified by slow blood flow and stagnant blood particles in the left atrium A Zingaro, Z Ahmad, CYA Pinto, K Sakata, EG Kholmovski, A Quarteroni, ... Heart Rhythm 20 (5), S161-S162, 2023 | 1 | 2023 |
| PO-05-009 COMBINED LEFT AND RIGHT ATRIAL NETWORK (CLARANET): A DEEP LEARNING (DL) MODEL FOR REPRODUCIBLE LGE-MRI AUTOMATIC SEGMENTATION OF LEFT AND RIGHT ATRIA (LA/RA) IN … A Lefebvre, K Sakata, CYA Pinto, I Vatsaraj, SY Ali, AY Rebecca, RL Ali, ... Heart Rhythm 21 (5), S553-S554, 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 |
| 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 |
| 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 |
| Convergence of Auditory Nerve Fibers onto Globular Bushy Cells M Kersting University of South Florida, 2020 | | 2020 |
Natalia TrayanovaJohns Hopkins UniversityVerified email at jhu.edu
