Jacob Tfelt-Hansen

M. Maleckar, L. Myklebust, J. J. Uv, P. M. Florvaag, V. Strøm, C. Glinge, R. Jabbari, N. Vejlstrup, T. Engstrøm, K. Ahtarovski, T. Jespersen, J. Tfelt-Hansen and H. Arevalo

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

Frontiers in physiology

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

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

Heart Rhythm

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

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

Computing in Cardiology, Singapore

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

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

Functional Imaging and Modelling of the Heart

M. Marciniak, H. Arevalo, J. Tfelt-Hansen, T. Jespersen, R. Jabbari, C. Glinge, K. A. Ahtarovski, N. Vejlstrup, M. Maleckar and K. S. Mcleod

From MR image to patient-specific simulation and population-based analysis:Tutorial for an openly available image-processing pipeline

MICCAI Workshop on Statistical Atlases and Cardiac Models of the Heart

L. Yuan, J. Koivumäki, B. Liang, L. G. Lorentzen, J. H. Svendsen, J. Tfelt-Hansen, M. Maleckar, N. Schmitt, M. S. Olesen and T. Jespersen

Investigations of the NaV\beta1b Sodium Channel Subunit in Human Ventricle; Functional Characterization of the H162P Brugada Syndrome Mutant

Heart and Circulatory Physiology