Bjørn-Jostein Singstad

B. Singstad, B. S. Dalen, S. Sihra, N. Forsch and S. Wall

Identifying Ionic Channel Block in a Virtual Cardiomyocyte Population Using Machine Learning Classifiers

Computational Physiology - Simula Summer School 2021 - Student Reports

B. Singstad, N. Azulay, A. Bjurstedt, S. S. Bjørndal, M. F. Drageseth, P. Engeset, K. Eriksen, M. Y. Gidey, E. O. Granum, M. G. Greaker, A. Grorud, S. O. Hewes, J. Hou, A. M. L. Recha, C. Matre, A. Seputis, S. E. Sørensen, V. Thøgersen, V. M. Joten, C. Tronstad and Ø. G. Martinsen

Estimation of heart rate variability from finger photoplethysmography during rest, mild exercise and mild mental stress

Journal of Electrical Bioimpedance

S. Hicks, D. Jha, V. Thambawita, P. Halvorsen, B. Singstad, S. Gaur, K. Pettersen, M. Goodwin, S. Parasa, T. de Lange and M. Riegler

MedAI: Transparency in Medical Image Segmentation

Nordic Machine Intelligence

B. Singstad, E. M. Muten and P. H. Brekke

Multi-Label ECG Classification Using Convolutional Neural Networks in a Classifier Chain

2021 Computing in Cardiology (CinC)2021 Computing in Cardiology (CinC)

N. P. P. TzavaraTzavara and B. Singstad

Transfer Learning in Polyp and Endoscopic Tool Segmentation from Colonoscopy Images

Nordic Machine Intelligence

B. Singstad

Sammenligning av kardiologisk og algoritmebasert EKG-tolkning på idrettsutøvere: Kan kunstig intelligens forbedre algoritmene?

The University of Oslo

B. Singstad and C. Tronstad

Convolutional Neural Network and Rule-Based Algorithms for Classifying 12-lead ECGs

2020 Computing in Cardiology Conference2020 Computing in Cardiology Conference (CinC)