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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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V. Thambawita, J. L. Isaksen, S. Hicks, J. Ghouse, G. Ahlberg, A. Linneberg, N. Grarup, C. Ellervik, M. S. Olesen, T. Hansen et al.

DeepFake electrocardiograms using generative adversarial networks are the beginning of the end for privacy issues in medicine

Nature Scientific Reports 11 (2021): 21896.
Journal Article
2021
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S. Fischer-Holzhausen, K. Yamamoto, M. P. Fjelstad and M. Maleckar

Probing the putative role of KATP channels and biological variability in a mathematical model of chondrocyte electrophysiology

Bioelectricity 3, no. 4 (2021): 272-281.
Journal Article
2021
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A. Mobasheri and M. Maleckar

The bioelectricity of connective tissue cells and their environments: bridging the gap

Bioelectricity 3 (2021): 241-242.
Journal Article
2021
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24 June 2020

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Export 12 results:
2021

Journal articles

S. Fischer-Holzhausen, K. Yamamoto, M. P. Fjelstad and M. Maleckar

Probing the putative role of KATP channels and biological variability in a mathematical model of chondrocyte electrophysiology

Bioelectricity 3, no. 4 (2021): 272-281.
Status: Published
S. Hicks, J. L. Isaksen, V. Thambawita, J. Ghouse, G. Ahlberg, A. Linneberg, N. Grarup, I. Strümke, C. Ellervik, M. S. Olesen et al.

Explaining deep neural networks for knowledge discovery in electrocardiogram analysis

Scientific Reports 11 (2021): 10949.
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
A. Mobasheri and M. Maleckar

The bioelectricity of connective tissue cells and their environments: bridging the gap

Bioelectricity 3 (2021): 241-242.
Status: Published
V. Thambawita, J. L. Isaksen, S. Hicks, J. Ghouse, G. Ahlberg, A. Linneberg, N. Grarup, C. Ellervik, M. S. Olesen, T. Hansen et al.

DeepFake electrocardiograms: the key for open science for artificial intelligence in medicine

Scientific Reports (2021).
Status: Accepted
V. Thambawita, J. L. Isaksen, S. Hicks, J. Ghouse, G. Ahlberg, A. Linneberg, N. Grarup, C. Ellervik, M. S. Olesen, T. Hansen et al.

DeepFake electrocardiograms using generative adversarial networks are the beginning of the end for privacy issues in medicine

Nature Scientific Reports 11 (2021): 21896.
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
2011

Journal articles

K. McDowell, H. Arevalo, M. Maleckar and N. A. Trayanova

Susceptibility to Reentry in the Infarcted Heart Depends on the Active Fibroblast Density

Biophysical Journal 110 (2011): 1307-15.
Status: Published
S. A. Niederer, E. Kerfoot, A. Benson, M. Bernabeu, O. Bernus, E. Cherry, R. Clayton, F. Fenton, A. Garny, E. Heidenreich et al.

N-Version Benchmark Evaluation of Cardiac Tissue Electrophysiology Simulators

Philosophical Transactions of the Royal Society A 369 (2011): 4331-51.
Status: Published
A. Tveito, G. T. Lines, O. Skavhaug and M. Maleckar

Unstable Eigenmodes As Possible Drivers for Cardiac Arrhythmias

Journal of the Royal Society Interface 8 (2011): 1212-6.
Status: Published