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Search results for biblio_year:1991
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M. E. Rognes, P. E. Farrell, S. W. Funke, J. E. Hake and M. Maleckar. "cbcbeat: an adjoint-enabled framework for computational cardiac electrophysiology." Journal of Open Source Software 2, no. 13 (2017).
S. Behdadfar, L. Navarro, J. Sundnes, M. Maleckar, S. Ross, H. H. Odland and S. Avril. "A Centerline Based Model Morphing Algorithm for Patient-Specific Finite Element Modelling of the Left Ventricle." IEEE Transactions on Biomedical Engineering (2017).
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).
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.
S. Kallhovd, M. Maleckar and M. E. Rognes. "Inverse estimation of cardiac activation times via gradient-based optimization." International Journal for Numerical Methods in Biomedical Engineering 34, no. 2 (2017): e2919.
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, Edited by M. Pop and G. Wright. Springer, 2017.
M. Maleckar, A. G. Edwards, W. Louch and G. T. Lines. "Studying dyadic structure-function relationships: a review of current modeling approaches and new insights into Ca2+ (mis)handling." Clinical Medicine Insights: Cardiology 11 (2017): 1-11.