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A. Storås, M. Magnø, F. Fineide, B. Thiede, X. Chen, I. Strümke, P. Halvorsen, T. Utheim and M. Riegler

Identifying Important Proteins in Meibomian Gland Dysfunction with Explainable Artificial Intelligence

In IEEE International Symposium on Computer-Based Medical Systems (IEEE CBMS2023), 2023.
Proceedings, refereed
2023
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C. Midoglu, A. Storås, S. S. Sabet, M. Hammou, S. Hicks, I. Strümke, M. Riegler, C. Griwodz and P. Halvorsen

Experiences and Lessons Learned from a Crowdsourced-Remote Hybrid User Survey Framework

In 2022 IEEE International Symposium on Multimedia (ISM). Italy: IEEE, 2022.
Proceedings, refereed
2022
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J. Amann, D. Vetter, S. N. Blomberg, H. C. Christensen, M. Coffee, S. Gerke, T. K. Gilbert, T. Hagendorff, S. Holm, M. Livne et al.

To explain or not to explain?—Artificial intelligence explainability in clinical decision support systems

PLOS Digital Health 1, no. 2 (2022): e0000016.
Journal Article
2022
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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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03 February 2022
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2023

Proceedings, refereed

A. Storås, M. Magnø, F. Fineide, B. Thiede, X. Chen, I. Strümke, P. Halvorsen, T. Utheim and M. Riegler

Identifying Important Proteins in Meibomian Gland Dysfunction with Explainable Artificial Intelligence

In IEEE International Symposium on Computer-Based Medical Systems (IEEE CBMS2023), 2023.
Status: Accepted
2022

Journal articles

J. Amann, D. Vetter, S. N. Blomberg, H. C. Christensen, M. Coffee, S. Gerke, T. K. Gilbert, T. Hagendorff, S. Holm, M. Livne et al.

To explain or not to explain?—Artificial intelligence explainability in clinical decision support systems

PLOS Digital Health 1, no. 2 (2022): e0000016.
Status: Published
S. Hicks, I. Strümke, V. Thambawita, M. Hammou, M. Riegler, P. Halvorsen and S. Parasa

On evaluation metrics for medical applications of artificial intelligence

Scientific Reports 12 (2022): 1-9.
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 og kvantitativ analyse innen velferd

Tidsskrift for velferdsforskning 25, no. 3 (2022): 1-24.
Status: Published

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 Proceedings of the 13th ACM Multimedia Systems Conference (MMSys '22). ACM, 2022.
Status: Published
C. Midoglu, A. Storås, S. S. Sabet, M. Hammou, S. Hicks, I. Strümke, M. Riegler, C. Griwodz and P. Halvorsen

Experiences and Lessons Learned from a Crowdsourced-Remote Hybrid User Survey Framework

In 2022 IEEE International Symposium on Multimedia (ISM). Italy: IEEE, 2022.
Status: Published
A. Storås, I. Strümke, M. Riegler and P. Halvorsen

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

In ACM Multimedia Systems (MMSys) Conference. ACM, 2022.
Status: Published
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: Published

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, Stavanger, Norway, 2022.
Status: Published