| Medai: Transparency in medical image segmentation S Hicks, D Jha, V Thambawita, P Halvorsen, BJ Singstad, S Gaur, ... Nordic Machine Intelligence 1 (1), 1-4, 2021 | 26 | 2021 |
| Convolutional neural network and rule-based algorithms for classifying 12-lead ECGs BJ Singstad, C Tronstad 2020 Computing in Cardiology, 1-4, 2020 | 23 | 2020 |
| Estimation of heart rate variability from finger photoplethysmography during rest, mild exercise and mild mental stress BJ Singstad, N Azulay, A Bjurstedt, SS Bjørndal, MF Drageseth, ... Journal of Electrical Bioimpedance 12 (1), 89-102, 2021 | 11 | 2021 |
| Assisted Cement Log Interpretation Using Machine Learning EM Viggen, BJ Singstad, E Time, S Mishra, E Berg SPE Drilling & Completion 38 (02), 220-234, 2023 | 9 | 2023 |
| Phonocardiogram classification using 1-dimensional inception time convolutional neural networks BJ Singstad, AM Gitau, MK Johnsen, J Ravn, LA Bongo, H Schirmer 2022 Computing in Cardiology (CinC) 498, 1-4, 2022 | 7 | 2022 |
| Multi-label ecg classification using convolutional neural networks in a classifier chain BJ Singstad, EM Muten, PH Brekke 2021 Computing in Cardiology (CinC) 48, 1-4, 2021 | 6 | 2021 |
| RoadAI: Reducing emissions in road construction S Riemer-Sørensen, HMB Holmestad, L Horn, K Michalowska, ... Nordic Machine Intelligence 3 (3), 4-4, 2023 | 4 | 2023 |
| Using deep convolutional neural networks to predict patients age based on ECGs from an independent test cohort BJ Singstad, B Tavashi Proceedings of the Northern Lights Deep Learning Workshop, 2022.10. 03.22280640, 2023 | 3 | 2023 |
| Transfer learning in polyp and endoscopic tool segmentation from colonoscopy images NP Tzavara, BJ Singstad Nordic Machine Intelligence 1 (1), 32-34, 2021 | 3 | 2021 |
| Deep learning for automated left ventricular outflow tract diameter measurements in 2D echocardiography SZ Zha, M Rogstadkjernet, LG Klæboe, H Skulstad, BJ Singstad, A Gilbert, ... Cardiovascular Ultrasound 21 (1), 19, 2023 | 1 | 2023 |
| Identifying ionic channel block in a virtual cardiomyocyte population using machine learning classifiers BJ Singstad, BS Dalen, S Sihra, N Forsch, S Wall Computational physiology, 91-109, 2022 | 1 | 2022 |
| Sammenligning av kardiologisk og algoritmebasert EKG-tolkning på idrettsutøvere: Kan kunstig intelligens forbedre algoritmene? BJ Singstad | 1 | 2021 |
| MemoryInception: Predicting Neurological Recovery from EEG Using Recurrent Inceptions BJ Singstad, J Ravn, A Ranjbar 2023 Computing in Cardiology (CinC) 50, 1-4, 2023 | | 2023 |
| Towards Invariant Soft Biometrics from Electrocardiograms A Ranjbar, BJ Singstad, J Ravn, H Schirmer 2023 Computing in Cardiology (CinC) 50, 1-4, 2023 | | 2023 |
| Insights from PTB-XL AM Gitau, A Adeyemi, B Tavashi, BJ Singstad | | 2023 |
| Assessing the Impact of Downsampled ECGs and Alternative Loss Functions in Multi-Label Classification of 12-Lead ECGs BJ Singstad, EM Muten medRxiv, 2022.11. 16.22282373, 2022 | | 2022 |
| Norwegian Endurance Athlete ECG Database BJ Singstad IEEE Open Journal of Engineering in Medicine and Biology 3, 162-166, 2022 | | 2022 |
| Design, development and testing of an analog ECG amplifier BJ Singstad Engineering Archive, 2020 | | 2020 |
| Programmere en aktiv bølgekompensator KP Fjørtoft, BJ Singstad | | 2014 |
Christian TronstadResearcher at Oslo University Hospital在 ous-hf.no 的电子邮件经过验证
