Convolutional Neural Network and Rule-Based Algorithms for Classifying 12-lead ECGs. - Bjørn-Jostein Singstad; Christian Tronstad (CinC, 2020)

Multi-Label ECG Classification Using Convolutional Neural Networks in a Classifier Chain. - Bjørn-Jostein Singstad; Eraraya Morenzo Muten; Pål Haugar Brekke (CinC, 2021)

Phonocardiogram Classification Using 1-Dimensional Inception Time Convolutional Neural Networks. - Bjørn-Jostein Singstad; Antony M. Gitau; Markus Kreutzer Johnsen; Johan Ravn; Lars Ailo Bongo; Henrik Schirmer (CinC, 2022)

Towards Invariant Soft Biometrics from Electrocardiograms. - Arian Ranjbar; Bjørn-Jostein Singstad; Jesper Ravn; Henrik Schirmer (CinC, 2023)

MemoryInception: Predicting Neurological Recovery from EEG Using Recurrent Inceptions. - Bjørn-Jostein Singstad; Jesper Ravn; Arian Ranjbar (CinC, 2023)

Using deep convolutional neural networks to predict patients age based on ECGs from an independent test cohort. - Bjørn-Jostein Singstad; Belal Tavashi (NLDL, 2023)

A deep learning based method for left ventricular strain measurements: repeatability and accuracy compared to experienced echocardiographers. - Magnus Rogstadkjernet; Sigurd Z. Zha; Lars G. Klæboe; Camilla K. Larsen; John M. Aalen; Esther Scheirlynck; Bjørn-Jostein Singstad; Steven Droogmans; Bernard Cosyns; Otto A. Smiseth; Kristina Hermann Haugaa; Thor Edvardsen; et al. (BMC Medical Imaging, 2024)