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A. Storås, A. Åsberg, P. Halvorsen, M. Riegler and I. Strümke

Predicting Tacrolimus Exposure in Kidney Transplanted Patients Using Machine Learning

In 35th IEEE CBMS International Symposium on Computer-Based Medical Systems. IEEE, 2022.
Proceedings, refereed
2022
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A. Storås, R. Prabhu, H. L. Hammer and I. Strümke

Bias i kvantitativ analyse innen velferd

Tidsskrift for velferdsforskning (2022).
Journal Article
2022
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A. Storås, I. Strümke, M. Riegler and P. Halvorsen

Research proposal: Explainability methods for machine learning systems for multimodal medical datasets

In ACM Multimedia Systems (MMSys) Conference. The ACM Multimedia Systems Conference (MMSys): ACM, 2022.
Proceedings, refereed
2022
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M. Hammou, C. Midoglu, S. Hicks, A. Storås, S. S. Sabet, I. Strümke, M. Riegler and P. Halvorsen

Huldra: A Framework for Collecting Crowdsourced Feedback on Multimedia Assets

In ACM Multimedia Systems (MMSys) Conference. The ACM Multimedia Systems Conference (MMSys): ACM, 2022.
Proceedings, refereed
2022
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03 February 2022
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SimulaMet part of EU project to improve patient outcome in acute stroke treatment

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2022

Journal articles

S. Hicks, I. Strümke, V. Thambawita, M. Hammou, M. Riegler, P. Halvorsen and S. Parasa

On evaluation metrics for medical applications of artificial intelligenceAbstract

Nature Scientific Reports 1236825221520218325484051210158697682437, no. 1 (2022).
Status: Published
A. Storås, I. Strümke, M. Riegler, J. Grauslund, H. L. Hammer, A. Yazidi, P. Halvorsen, K. G. Gundersen, T. P. Utheim and C. J. Jackson

Artificial intelligence in dry eye disease

The Ocular Surface 23 (2022): 74-86.
Status: Published
A. Storås, R. Prabhu, H. L. Hammer and I. Strümke

Bias i kvantitativ analyse innen velferd

Tidsskrift for velferdsforskning (2022).
Status: Accepted

Proceedings, refereed

M. Hammou, C. Midoglu, S. Hicks, A. Storås, S. S. Sabet, I. Strümke, M. Riegler and P. Halvorsen

Huldra: A Framework for Collecting Crowdsourced Feedback on Multimedia Assets

In ACM Multimedia Systems (MMSys) Conference. The ACM Multimedia Systems Conference (MMSys): ACM, 2022.
Status: Accepted
A. Storås, I. Strümke, M. Riegler and P. Halvorsen

Research proposal: Explainability methods for machine learning systems for multimodal medical datasets

In ACM Multimedia Systems (MMSys) Conference. The ACM Multimedia Systems Conference (MMSys): ACM, 2022.
Status: Accepted
A. Storås, A. Åsberg, P. Halvorsen, M. Riegler and I. Strümke

Predicting Tacrolimus Exposure in Kidney Transplanted Patients Using Machine Learning

In 35th IEEE CBMS International Symposium on Computer-Based Medical Systems. IEEE, 2022.
Status: Accepted

Posters

A. Storås, M. Riegler, P. Halvorsen, A. Åsberg and I. Strümke

Predicting drug exposure in kidney transplanted patients using machine learning

NORA Annual Conference 2022, 2022.
Status: Accepted
2021

Journal articles

S. Hicks, J. L. Isaksen, V. Thambawita, J. Ghouse, G. Ahlberg, A. Linneberg, N. Grarup, I. Strümke, C. Ellervik, M. S. Olesen et al.

Explaining deep neural networks for knowledge discovery in electrocardiogram analysis

Scientific Reports 11 (2021): 10949.
Status: Published
V. Thambawita, I. Strümke, S. Hicks, P. Halvorsen, S. Parasa and M. Riegler

Impact of Image Resolution on Deep Learning Performance in Endoscopy Image Classification: An Experimental Study Using a Large Dataset of Endoscopic Images

Diagnostics 11, no. 12 (2021).
Status: Published
V. Thambawita, J. L. Isaksen, S. Hicks, J. Ghouse, G. Ahlberg, A. Linneberg, N. Grarup, C. Ellervik, M. S. Olesen, T. Hansen et al.

DeepFake electrocardiograms using generative adversarial networks are the beginning of the end for privacy issues in medicine

Nature Scientific Reports 11 (2021): 21896.
Status: Published