@inbook {43018,
	title = {Smittestopp for Android and iOS},
	booktitle = {Smittestopp - A Case Study on Digital Contact Tracing},
	volume = {11},
	year = {2022},
	pages = {11 - 27},
	publisher = {Springer International Publishing},
	organization = {Springer International Publishing},
	address = {Cham},
	isbn = {978-3-031-05465-5},
	issn = {2512-1677},
	doi = {10.1007/978-3-031-05466-210.1007/978-3-031-05466-2_2},
	url = {https://link.springer.com/content/pdf/10.1007/978-3-031-05466-2_2},
	author = {Per Magne {Florvaag} and Kjeldsberg, Henrik and Sebastian Kenji {Mitusch}},
	editor = {Elmokashfi, Ahmed and Lysne, Olav and Naumova, Valeriya}
}
@misc {maleckar2021b,
	title = {B-PO02-022 Combining simulation and machine learning to accurately predict arrhythmic risk in post-infarction patients},
	howpublished = {Heart Rhythm},
	volume = {18},
	number = {8},
	year = {2021},
	pages = {S104},
	publisher = {Elsevier},
	address = {Boston, MA},
	author = {Maleckar, Molly and Per Magne {Florvaag} and Str{\o}m, Vilde and Glinge, Charlotte and Jabbari, Reza and Vejlstrup, Niels and Engstrom, Thomas and Kiril A. {Ahtarovski} and Jespersen, Thomas and Tfelt-Hansen, Jacob and Arevalo, Hermenegild}
}
@article {maleckar2021combined,
	title = {Combined In-silico and Machine Learning Approaches Toward Predicting Arrhythmic Risk in Post-infarction Patients},
	journal = {Frontiers in physiology},
	volume = {12},
	year = {2021},
	pages = {745349},
	publisher = {Frontiers},
	author = {Maleckar, Molly and Myklebust, Lena and Julie Johanne {Uv} and Per Magne {Florvaag} and Str{\o}m, Vilde and Glinge, Charlotte and Jabbari, Reza and Vejlstrup, Niels and Engstr{\o}m, Thomas and Ahtarovski, Kiril and Jespersen, Thomas and Tfelt-Hansen, Jacob and Arevalo, Hermenegild}
}
@article {28029,
	title = {Nationwide rollout reveals efficacy of epidemic control through digital contact tracing},
	journal = {Nature Communications},
	volume = {12},
	number = {5918},
	year = {2021},
	publisher = {Springer Nature},
	doi = {https://doi.org/10.1038/s41467-021-26144-8},
	author = {Elmokashfi, Ahmed and Sundnes, Joakim and Kvalbein, Amund and Naumova, Valeriya and Reinemo, Sven-Arne and Per Magne {Florvaag} and H{\r a}kon Kvale {Stensland} and Lysne, Olav}
}
@inproceedings {26548,
	title = {Automated and objective segmentation of medical image using machine learning techniques: all models are wrong, but some are useful},
	journal = {Computational and Mathematical Biomedical Engineering},
	year = {2019},
	publisher = {CMBE},
	address = {Sendai, Japan},
	abstract = {Medical images are the basis of {\textquotedblright}patient-specific{\textquotedblright} simulations but come with severe limitations, most notably through operator dependencies like image segmentation. The aim was to develop an open- source pipeline for automated and objective segmentation. Combining latest advances from machine learning and signal processing, we demonstrate that the pipeline preserve all major characteristic features of a test image and identify minor branches, which can be further modified by the user. In conclusion, the default pipeline will in the majority of cases offer labor free automated and objective segmentation, or at worst provide an optimal starting point for manual segmentation.},
	author = {Per Magne {Florvaag} and Naumova, Valeriya and Valen-Sendstad, Kristian}
}
@misc {27158,
	title = {A Combined In-Silico and Machine Learning Approach towards Predicting Arrhythmic Risk in Post-Infarction Patients},
	howpublished = {Computing in Cardiology, Singapore},
	year = {2019},
	author = {Per Magne {Florvaag} and Str{\o}m, Vilde and Glinge, Charlotte and Jabbari, Reza and Vejlstrup, Niels and Engstrom, Thomas and Kiril A. {Ahtarovski} and Jespersen, Thomas and Tfelt-Hansen, Jacob and Naumova, Valeriya and Arevalo, Hermenegild}
}
