Per Magne Florvaag

P. M. Florvaag, H. Kjeldsberg and S. K. Mitusch

Smittestopp for Android and iOS

Smittestopp − A Case Study on Digital Contact Tracing

A. Elmokashfi, J. Sundnes, A. Kvalbein, V. Naumova, S. Reinemo, P. M. Florvaag, H. K. Stensland and O. Lysne

Nationwide rollout reveals efficacy of epidemic control through digital contact tracing

Nature Communications

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

P. M. Florvaag, V. Naumova and K. Valen-Sendstad

Automated and objective segmentation of medical image using machine learning techniques: all models are wrong, but some are useful

Computational and Mathematical Biomedical Engineering