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Most recent publications

M. Maleckar, L. Myklebust, J. J. Uv, P. M. Florvaag, V. Strøm, C. Glinge, R. Jabbari, N. Vejlstrup, T. Engstrøm, K. Ahtarovski et al.

Combined In-silico and Machine Learning Approaches Toward Predicting Arrhythmic Risk in Post-infarction Patients

Frontiers in physiology 12 (2021): 745349.
Journal Article
2021
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M. Vagos, H. Arevalo, J. Heijman, U. Schotten and J. Sundnes

A computational study of the effects of tachycardia-induced remodelling on calcium wave propagation in rabbit atrial myocytes

Frontiers in Physiology 12 (2021).
Journal Article
2021
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M. Albatat, H. Arevalo, J. Bergsland, V. Strøm, I. Balasingham and H. H. Odland

Optimal pacing sites in cardiac resynchronization by left ventricular activation front analysis

Computers in Biology and Medicine 128 (2021): 104159.
Journal Article
2021
View
M. R. Vagos, H. Arevalo, B. L. de Oliveira, J. Sundnes and M. Maleckar

A computational framework for testing arrhythmia marker sensitivities to model parameters in functionally calibrated populations of atrial cells

Chaos: An Interdisciplinary Journal of Nonlinear Science 27 (2017): 093941.
Journal Article
2017
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Selected publications

H. Arevalo, F. Vadakkumpadan, E. Guallar, A. Jebb, P. Malamas, K. C. Wu and N. A. Trayanova

Arrhythmia risk stratification of patients after myocardial infarction using personalized heart models

Nature Communications 7 (2016).
Journal Article
2016
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A. Prakosa, H. Arevalo, D. Deng, P. M. Boyle, P. P. Nikolov, H. Ashikaga, J. J. E. Blauer, E. Ghafoori, C. J. Park, R. C. Blake et al.

Personalized virtual-heart technology for guiding the ablation of infarct-related ventricular tachycardia

Nature Biomedical Engineering 2 (2018): 732-740.
Journal Article
2018
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News

05 September 2023

Simula hosts Inria guests to discuss current & future collaboration

Background

PhD in Biomedical Engineering
Johns Hopkins University
May 2014

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Export 11 results:
2021

Journal articles

M. Albatat, H. Arevalo, J. Bergsland, V. Strøm, I. Balasingham and H. H. Odland

Optimal pacing sites in cardiac resynchronization by left ventricular activation front analysis

Computers in Biology and Medicine 128 (2021): 104159.
Status: Published
M. Maleckar, L. Myklebust, J. J. Uv, P. M. Florvaag, V. Strøm, C. Glinge, R. Jabbari, N. Vejlstrup, T. Engstrøm, K. Ahtarovski et al.

Combined In-silico and Machine Learning Approaches Toward Predicting Arrhythmic Risk in Post-infarction Patients

Frontiers in physiology 12 (2021): 745349.
Status: Published
M. Vagos, H. Arevalo, J. Heijman, U. Schotten and J. Sundnes

A computational study of the effects of tachycardia-induced remodelling on calcium wave propagation in rabbit atrial myocytes

Frontiers in Physiology 12 (2021).
Status: Published

Posters

M. Maleckar, P. M. Florvaag, V. Strøm, C. Glinge, R. Jabbari, N. Vejlstrup, T. Engstrom, K. A. Ahtarovski, T. Jespersen, J. Tfelt-Hansen et al.

B-PO02-022 Combining simulation and machine learning to accurately predict arrhythmic risk in post-infarction patients

In Heart Rhythm. Vol. 18. Boston, MA: Elsevier, 2021.
Status: Published
2017

Journal articles

J. Dhamala, H. Arevalo, J. Sapp, M. Horacek, K. C. Wu, N. A. Trayanova and L. Wang

Spatially Adaptive Multi-Scale Optimization for Local Parameter Estimation in Cardiac Electrophysiology

IEEE Transactions on Medical Imaging 36, no. 9 (2017): 1966-1978.
Status: Published
M. R. Vagos, H. Arevalo, B. L. de Oliveira, J. Sundnes and M. Maleckar

A computational framework for testing arrhythmia marker sensitivities to model parameters in functionally calibrated populations of atrial cells

Chaos: An Interdisciplinary Journal of Nonlinear Science 27 (2017): 093941.
Status: Published
M. Vagos, H. Arevalo, B. L. de Oliveira, J. Sundnes and M. Maleckar

A computational framework for testing arrhythmia marker sensitivities to model parameters in functionally calibrated populations of atrial cells

Chaos 27, no. 9 (2017).
Status: Published

Proceedings, refereed

M. Marciniak, H. Arevalo, J. Tfelt-Hansen, K. A. Ahtarovski, T. Jespersen, R. Jabbari, C. Glinge, N. Vejlstrup, T. Engstrom, M. Maleckar et al.

A multiple kernel learning framework to investigate the relationship between ventricular fibrillation and first myocardial infarction

In International Conference on Functional Imaging and Modeling of the Heart. {Springer, Cham, 2017.
Status: Published
M. Marciniak, H. Arevalo, J. Tfelt-Hansen, K. A. Ahtarovski, T. Jespersen, R. Jabbari, C. Glinge, N. Vejlstrup, T. Engstrom, M. Maleckar et al.

A multiple kernel learning framework to investigate the relationship between ventricular fibrillation and first myocardial infarction

In Functional Imaging and Modelling of the Heart. Springer, 2017.
Status: Published

Posters

M. Vagos, H. Arevalo, F. Sacco and M. Maleckar

A data-driven framework uncovers arrhythmogenic mechanisms in a 'functionally calibrated' population of models

Biophysical Society 61st Annual Meeting, New Orleans, Louisiana, USA, 2017.
Status: Published