@article {ALBATAT2021104159,
	title = {Optimal pacing sites in cardiac resynchronization by left ventricular activation front analysis},
	journal = {Computers in Biology and Medicine},
	volume = {128},
	year = {2021},
	pages = {104159},
	publisher = {Elsevier},
	abstract = {Cardiac resynchronization therapy (CRT) can substantially improve dyssynchronous heart failure and reduce mortality. However, about one-third of patients who are implanted, derive no measurable benefit from CRT. Non-response may partly be due to suboptimal activation of the left ventricle (LV) caused by electrophysiological heterogeneities. The goal of this study is to investigate the performance of a newly developed method used to analyze electrical wavefront propagation in a heart model including myocardial scar and compare this to clinical benchmark studies. We used computational models to measure the maximum activation front (MAF) in the LV during different pacing scenarios. Different heart geometries and scars were created based on cardiac MR images of three patients. The right ventricle (RV) was paced from the apex and the LV was paced from 12 different sites, single site, dual-site and triple site. Our results showed that for single LV site pacing, the pacing site with the largest MAF corresponded with the latest activated regions of the LV demonstrated during RV pacing, which also agrees with previous markers used for predicting optimal single-site pacing location. We then demonstrated the utility of MAF in predicting optimal electrode placements in more complex scenarios including scar and multi-site LV pacing. This study demonstrates the potential value of computational simulations in understanding and planning CRT.},
	keywords = {Cardiac resynchronization therapy, Cardiology, Computational modeling, electrophysiology, Heart failure},
	issn = {0010-4825},
	doi = {https://doi.org/10.1016/j.compbiomed.2020.104159},
	url = {http://www.sciencedirect.com/science/article/pii/S001048252030490X},
	author = {Albatat, Mohammad and Arevalo, Hermenegild and Bergsland, Jacob and Str{\o}m, Vilde and Balasingham, Ilangko and Hans Henrik {Odland}}
}
@article {27766,
	title = {Using Jupyter for reproducible scientific workflows},
	journal = {Computing in Science \& Engineering},
	volume = {23},
	year = {2021},
	month = {Jan-01-2021},
	pages = {36-46},
	publisher = {IEEE},
	abstract = {Literate computing has emerged as an important tool for computational studies and open science, with growing folklore of best practices. In this work, we report two case studies - one in computational magnetism and another in computational mathematics - where a dedicated software was exposed into the Jupyter environment. This enabled interactive and batch computational exploration of data, simulations, data analysis, and workflow documentation and outcome in Jupyter notebooks. In the first study, Ubermag drives existing computational micromagnetics software through a domain-specific language embedded in Python. In the second study, a dedicated Jupyter kernel interfaces with the GAP system for computational discrete algebra and its dedicated programming language. In light of these case studies, we discuss the benefits of this approach, including progress towards more reproducible and re-usable research results and outputs, notably through the use of infrastructure such as JupyterHub and Binder.},
	keywords = {Analytical models, Computational modeling, Documentation, Kernel, Libraries, python, Tools},
	issn = {1521-9615},
	doi = {10.1109/MCSE.2021.3052101},
	url = {https://ieeexplore.ieee.org/document/9325550},
	author = {Beg, Marijan and Belin, Juliette and Kluyver, Thomas and Konovalov, Alexander and Ragan-Kelley, Benjamin and Thiery, Nicolas and Fangohr, Hans}
}
@inproceedings {7391416,
	title = {Localization and not extent of fibrofatty infiltratio is the primary factor determining conduction disturbance in a computational model of arrhythmogenic cardiomyopathy},
	journal = {2015 E-Health and Bioengineering Conference (EHB)},
	year = {2015},
	month = {Nov},
	pages = {1-6},
	publisher = {ACM IEEE},
	keywords = {action potential, activation sites, arrhythmogenic cardiomyopathy, bioelectric potentials, biological tissues, biomedical MRI, biomembranes, cardiovascular system, cellular biophysics, computational model, Computational modeling, conduction disturbance, conduction properties, disease progression, diseases, electrophysiology, fibrofatty diseased tissue location, fibrofatty infiltration localization, fibrofatty patterns, fibrofatty region, Geometry, global conduction velocity, Heart, human electrophysiology, intercellular junctions, Junctions, Magnetic resonance imaging, Morphology, nonviable tissue, organ-level model, passive membrane, patient heart geometry, physiological models},
	doi = {10.1109/EHB.2015.7391416},
	author = {Kallhovd, Siri and S. U. {Gjerald} and Wall, Samuel and Saberniak, J. and Haugaa, K. and Maleckar, Molly}
}
