Michael J. Murphy

Computationally guided personalized targeted ablation of persistent atrial fibrillation

Stefan L. Zimmerman, Rheeda L. Ali, David D Spragg, 2019, Nature Biomedical Engineering.

Arrhythmia dynamics in computational models of the atria following virtual ablation of re-entrant drivers.

N. Trayanova, P. Boyle, Joe B Hakim, 2018, Europace : European pacing, arrhythmias, and cardiac electrophysiology : journal of the working groups on cardiac pacing, arrhythmias, and cardiac cellular electrophysiology of the European Society of Cardiology.

The Fibrotic Substrate in Persistent Atrial Fibrillation Patients: Comparison Between Predictions From Computational Modeling and Measurements From Focal Impulse and Rotor Mapping

N. Trayanova, H. Calkins, H. Ashikaga, 2018, Front. Physiol..

Cytokine RNA In Situ Hybridization Permits Individualized Molecular Phenotyping in Biopsies of Psoriasis and Atopic Dermatitis

C. Ko, M. Bosenberg, J. McNiff, 2021, JID innovations.

Sensitivity of reentrant driver localization to electrophysiological parameter variability in image-based computational models of persistent atrial fibrillation sustained by a fibrotic substrate.

Natalia A Trayanova, Dongdong Deng, Farhad Pashakhanloo, 2017, Chaos.

Termination of re‐entrant atrial tachycardia via optogenetic stimulation with optimized spatial targeting: insights from computational models

Thomas V. Karathanos, Natalia A Trayanova, Patrick M Boyle, 2018, The Journal of physiology.

Comparing Reentrant Drivers Predicted by Image-Based Computational Modeling and Mapped by Electrocardiographic Imaging in Persistent Atrial Fibrillation

N. Trayanova, M. Hocini, M. Haïssaguerre, 2018, Front. Physiol..