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For: Plank G, Loewe A, Neic A, Augustin C, Huang YL, Gsell MAF, Karabelas E, Nothstein M, Prassl AJ, Sánchez J, Seemann G, Vigmond EJ. The openCARP simulation environment for cardiac electrophysiology. Comput Methods Programs Biomed 2021;208:106223. [PMID: 34171774 DOI: 10.1016/j.cmpb.2021.106223] [Cited by in Crossref: 25] [Cited by in F6Publishing: 14] [Article Influence: 12.5] [Reference Citation Analysis]
Number Citing Articles
1 Petras A, Gsell MAF, Augustin CM, Rodriguez-Padilla J, Jung A, Strocchi M, Prinzen FW, Niederer SA, Plank G, Vigmond EJ. Mechanoelectric effects in healthy cardiac function and under Left Bundle Branch Block pathology. Comput Biol Med 2023;156:106696. [PMID: 36870172 DOI: 10.1016/j.compbiomed.2023.106696] [Reference Citation Analysis]
2 Schwarz EL, Pegolotti L, Pfaller MR, Marsden AL. Beyond CFD: Emerging methodologies for predictive simulation in cardiovascular health and disease. Biophys Rev (Melville) 2023;4:011301. [PMID: 36686891 DOI: 10.1063/5.0109400] [Reference Citation Analysis]
3 Thangamani A, Jost TT, Loechner V, Genaud S, Bramas B. Lifting Code Generation of Cardiac Physiology Simulation to Novel Compiler Technology. Proceedings of the 21st ACM/IEEE International Symposium on Code Generation and Optimization 2023. [DOI: 10.1145/3579990.3580008] [Reference Citation Analysis]
4 Lindner LP, Gerach T, Jahnke T, Loewe A, Weiss D, Wieners C. Efficient time splitting schemes for the monodomain equation in cardiac electrophysiology. Int J Numer Method Biomed Eng 2023;39:e3666. [PMID: 36562492 DOI: 10.1002/cnm.3666] [Reference Citation Analysis]
5 Ramlugun GS, Kulkarni K, Pallares-Lupon N, Boukens BJ, Efimov IR, Vigmond EJ, Bernus O, Walton RD. A comprehensive framework for evaluation of high pacing frequency and arrhythmic optical mapping signals. Front Physiol 2023;14:734356. [PMID: 36755791 DOI: 10.3389/fphys.2023.734356] [Reference Citation Analysis]
6 Rinné S, Oertli A, Nagel C, Tomsits P, Jenewein T, Kääb S, Kauferstein S, Loewe A, Beckmann BM, Decher N. Functional Characterization of a Spectrum of Novel Romano-Ward Syndrome KCNQ1 Variants. Int J Mol Sci 2023;24. [PMID: 36674868 DOI: 10.3390/ijms24021350] [Reference Citation Analysis]
7 Finsberg HNT, van Herck IGM, Daversin-catty C, Arevalo H, Wall S. simcardems: A FEniCS-based cardiac electro-mechanics solver. JOSS 2023;8:4753. [DOI: 10.21105/joss.04753] [Reference Citation Analysis]
8 Rodero C, Longobardi S, Augustin C, Strocchi M, Plank G, Lamata P, Niederer SA. Calibration of Cohorts of Virtual Patient Heart Models Using Bayesian History Matching. Ann Biomed Eng 2023;51:241-52. [PMID: 36271218 DOI: 10.1007/s10439-022-03095-9] [Reference Citation Analysis]
9 Ricci E, Bartolucci C, Severi S. The virtual sinoatrial node: What did computational models tell us about cardiac pacemaking? Prog Biophys Mol Biol 2023;177:55-79. [PMID: 36374743 DOI: 10.1016/j.pbiomolbio.2022.10.008] [Reference Citation Analysis]
10 Amsaleg A, Sánchez J, Mikut R, Loewe A. Characterization of the pace-and-drive capacity of the human sinoatrial node: A 3D in silico study. Biophys J 2022;121:4247-59. [PMID: 36262044 DOI: 10.1016/j.bpj.2022.10.020] [Reference Citation Analysis]
11 Zhu C, Vedula V, Parker D, Wilson N, Shadden S, Marsden A. svFSI: A Multiphysics Package for Integrated Cardiac Modeling. JOSS 2022;7:4118. [DOI: 10.21105/joss.04118] [Cited by in F6Publishing: 1] [Reference Citation Analysis]
12 Coveney S, Roney CH, Corrado C, Wilkinson RD, Oakley JE, Niederer SA, Clayton RH. Calibrating cardiac electrophysiology models using latent Gaussian processes on atrial manifolds. Sci Rep 2022;12:16572. [PMID: 36195766 DOI: 10.1038/s41598-022-20745-z] [Reference Citation Analysis]
13 Gillette K, Gsell MAF, Strocchi M, Grandits T, Neic A, Manninger M, Scherr D, Roney CH, Prassl AJ, Augustin CM, Vigmond EJ, Plank G. A personalized real-time virtual model of whole heart electrophysiology. Front Physiol 2022;13:907190. [DOI: 10.3389/fphys.2022.907190] [Cited by in F6Publishing: 1] [Reference Citation Analysis]
14 Rappel WJ. The physics of heart rhythm disorders. Phys Rep 2022;978:1-45. [PMID: 36843637 DOI: 10.1016/j.physrep.2022.06.003] [Cited by in Crossref: 3] [Cited by in F6Publishing: 3] [Article Influence: 3.0] [Reference Citation Analysis]
15 Lange M, Kwan E, Dosdall DJ, Macleod RS, Bunch TJ, Ranjan R. Case report: Personalized computational model guided ablation for left atrial flutter. Front Cardiovasc Med 2022;9. [DOI: 10.3389/fcvm.2022.893752] [Reference Citation Analysis]
16 Coveney S, Cantwell C, Roney C. Atrial conduction velocity mapping: clinical tools, algorithms and approaches for understanding the arrhythmogenic substrate. Med Biol Eng Comput 2022;60:2463-78. [PMID: 35867323 DOI: 10.1007/s11517-022-02621-0] [Cited by in Crossref: 2] [Article Influence: 2.0] [Reference Citation Analysis]
17 Goette A, Rickert V, Brandner S. Simulatoren und Simulatortraining in der interventionellen Elektrophysiologie. Herzschr Elektrophys 2022;33:351-354. [DOI: 10.1007/s00399-022-00882-8] [Reference Citation Analysis]
18 Azzolin L, Eichenlaub M, Nagel C, Nairn D, Sanchez J, Unger L, Dössel O, Jadidi A, Loewe A. Personalized ablation vs. conventional ablation strategies to terminate atrial fibrillation and prevent recurrence. Europace 2023;25:211-22. [PMID: 35943361 DOI: 10.1093/europace/euac116] [Cited by in Crossref: 5] [Cited by in F6Publishing: 5] [Article Influence: 5.0] [Reference Citation Analysis]
19 Hustad KG, Cai X. Resource-Efficient Use of Modern Processor Architectures For Numerically Solving Cardiac Ionic Cell Models. Front Physiol 2022;13:904648. [DOI: 10.3389/fphys.2022.904648] [Reference Citation Analysis]
20 Amsaleg A, Sánchez J, Mikut R, Loewe A. Characterization of the Pace-and-Drive Capacity of the Human Sinoatrial Node: a 3D in silico Study.. [DOI: 10.1101/2022.06.03.494644] [Reference Citation Analysis]
21 Sánchez J, Loewe A. A Review of Healthy and Fibrotic Myocardium Microstructure Modeling and Corresponding Intracardiac Electrograms. Front Physiol 2022;13:908069. [DOI: 10.3389/fphys.2022.908069] [Reference Citation Analysis]
22 Karabelas E, Gsell MA, Haase G, Plank G, Augustin CM. An accurate, robust, and efficient finite element framework with applications to anisotropic, nearly and fully incompressible elasticity. Computer Methods in Applied Mechanics and Engineering 2022;394:114887. [DOI: 10.1016/j.cma.2022.114887] [Cited by in Crossref: 2] [Cited by in F6Publishing: 2] [Article Influence: 2.0] [Reference Citation Analysis]
23 Campos FO, Neic A, Mendonca Costa C, Whitaker J, O’neill M, Razavi R, Rinaldi CA, Scherr D, Niederer SA, Plank G, Bishop MJ. An automated near-real time computational method for induction and treatment of scar-related ventricular tachycardias. Medical Image Analysis 2022. [DOI: 10.1016/j.media.2022.102483] [Reference Citation Analysis]
24 Serra D, Romero P, Garcia-fernandez I, Lozano M, Liberos A, Rodrigo M, Bueno-orovio A, Berruezo A, Sebastian R. An Automata-Based Cardiac Electrophysiology Simulator to Assess Arrhythmia Inducibility. Mathematics 2022;10:1293. [DOI: 10.3390/math10081293] [Reference Citation Analysis]
25 Ryzhii M, Ryzhii E. Pacemaking function of two simplified cell models. PLoS ONE 2022;17:e0257935. [DOI: 10.1371/journal.pone.0257935] [Reference Citation Analysis]
26 Sutanto H, Heijman J. Integrative Computational Modeling of Cardiomyocyte Calcium Handling and Cardiac Arrhythmias: Current Status and Future Challenges. Cells 2022;11:1090. [DOI: 10.3390/cells11071090] [Cited by in Crossref: 3] [Cited by in F6Publishing: 3] [Article Influence: 3.0] [Reference Citation Analysis]
27 Jung A, Gsell MAF, Augustin CM, Plank G. An Integrated Workflow for Building Digital Twins of Cardiac Electromechanics—A Multi-Fidelity Approach for Personalising Active Mechanics. Mathematics 2022;10:823. [DOI: 10.3390/math10050823] [Cited by in Crossref: 7] [Cited by in F6Publishing: 7] [Article Influence: 7.0] [Reference Citation Analysis]
28 Azzolin L, Eichenlaub M, Nagel C, Nairn D, Sánchez J, Unger L, Dössel O, Jadidi A, Loewe A. AugmentA: Patient-specific Augmented Atrial model Generation Tool.. [DOI: 10.1101/2022.02.13.22270835] [Reference Citation Analysis]
29 Tong L, Zhao C, Fu Z, Dong R, Wu Z, Wang Z, Zhang N, Wang X, Cao B, Sun Y, Zheng D, Xia L, Deng D. Preliminary Study: Learning the Impact of Simulation Time on Reentry Location and Morphology Induced by Personalized Cardiac Modeling. Front Physiol 2021;12:733500. [PMID: 35002750 DOI: 10.3389/fphys.2021.733500] [Reference Citation Analysis]
30 Loewe A, Martínez Díaz P, Nagel C, Sánchez J. Cardiac Digital Twin Modeling. Innovative Treatment Strategies for Clinical Electrophysiology 2022. [DOI: 10.1007/978-981-19-6649-1_7] [Reference Citation Analysis]
31 Maleckar MM, Myklebust L, Uv J, Florvaag PM, Strøm V, Glinge C, Jabbari R, Vejlstrup N, Engstrøm T, Ahtarovski K, Jespersen T, Tfelt-Hansen J, Naumova V, Arevalo H. Combined In-silico and Machine Learning Approaches Toward Predicting Arrhythmic Risk in Post-infarction Patients. Front Physiol 2021;12:745349. [PMID: 34819872 DOI: 10.3389/fphys.2021.745349] [Cited by in Crossref: 2] [Cited by in F6Publishing: 2] [Article Influence: 1.0] [Reference Citation Analysis]
32 Sánchez J, Trenor B, Saiz J, Dössel O, Loewe A. Fibrotic Remodeling during Persistent Atrial Fibrillation: In Silico Investigation of the Role of Calcium for Human Atrial Myofibroblast Electrophysiology. Cells 2021;10:2852. [PMID: 34831076 DOI: 10.3390/cells10112852] [Cited by in Crossref: 2] [Cited by in F6Publishing: 3] [Article Influence: 1.0] [Reference Citation Analysis]
33 Ryzhii M, Ryzhii E. Pacemaking function of two simplified cell models.. [DOI: 10.1101/2021.09.14.460406] [Reference Citation Analysis]
34 Azzolin L, Nagel C, Nairn D, Sanchez J, Zheng T, Eichenlaub M, Jadidi A, Dossel O, Loewe A. Automated Framework for the Augmentation of Missing Anatomical Structures and Generation of Personalized Atrial Models from Clinical Data. 2021 Computing in Cardiology (CinC) 2021. [DOI: 10.23919/cinc53138.2021.9662846] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 0.5] [Reference Citation Analysis]
35 Dössel O, Luongo G, Nagel C, Loewe A. Computer Modeling of the Heart for ECG Interpretation—A Review. Hearts 2021;2:350-68. [DOI: 10.3390/hearts2030028] [Cited by in Crossref: 5] [Cited by in F6Publishing: 5] [Article Influence: 2.5] [Reference Citation Analysis]
36 Coveney S, Corrado C, Oakley JE, Wilkinson RD, Niederer SA, Clayton RH. Bayesian Calibration of Electrophysiology Models Using Restitution Curve Emulators. Front Physiol 2021;12:693015. [PMID: 34366883 DOI: 10.3389/fphys.2021.693015] [Cited by in Crossref: 3] [Cited by in F6Publishing: 5] [Article Influence: 1.5] [Reference Citation Analysis]