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Most recent publications

J. Langguth, H. Arevalo, K. G. Hustad and X. Cai

Towards Detailed Real-Time Simulations of Cardiac Arrhythmia

In Computing in Cardiology. Vol. 46. IEEE, 2019.
Proceedings, refereed
2019
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H. Arevalo, K. H. Jæger and S. Wall

Investigating the Pro- and Anti-Arrhythmic Properties of Human Induced Pluripotent Stem Cell-Derived Cardiomyocytes in Post-Infarction Patient Hearts: A Modeling Study

In 6th International Conference on Computational and Mathematical Biomedical Engineering. Vol. 1. Zeta Computational Resources Ltd, 2019.
Proceedings, refereed
2019
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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).
Journal Article
2017
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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.
Proceedings, refereed
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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Background

PhD in Biomedical Engineering
Johns Hopkins University
May 2014

Available Master's topics

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2019

Proceedings, refereed

H. Arevalo, K. H. Jæger and S. Wall

Investigating the Pro- and Anti-Arrhythmic Properties of Human Induced Pluripotent Stem Cell-Derived Cardiomyocytes in Post-Infarction Patient Hearts: A Modeling Study

In 6th International Conference on Computational and Mathematical Biomedical Engineering. Vol. 1. Zeta Computational Resources Ltd, 2019.
Status: Published
J. Langguth, H. Arevalo, K. G. Hustad and X. Cai

Towards Detailed Real-Time Simulations of Cardiac Arrhythmia

In Computing in Cardiology. Vol. 46. IEEE, 2019.
Status: Published

Posters

J. Langguth, H. Arevalo, K. G. Hustad and X. Cai

Towards Detailed Real-Time Simulations of Cardiac Arrhythmia

International Conference in Computing in Cardiology, Singapore, 2019.
Status: Published

Talks, contributed

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

A Combined In-Silico and Machine Learning Approach towards Predicting Arrhythmic Risk in Post-Infarction Patients

In Computing in Cardiology, Singapore, 2019.
Status: Published
2017

Journal articles

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 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