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A. Storås, O. E. Andersen, S. Lockhart, R. Thielemann, F. Gnesin, V. Thambawita, S. Hicks, J. Kanters, I. Strümke, P. Halvorsen et al.

Usefulness of Heat Map Explanations for Deep-Learning-Based Electrocardiogram Analysis

Diagnostics 13, no. 14 (2023).
Journal Article
2023
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F. Fineide, A. Storås, M. Magnø, H. L. Hammer, X. Chen, A. Khan, P. Halvorsen, T. Utheim and M. Riegler

Predicting the degree of meibomian gland dropout with artificial intelligence

In ARVO Annual Meeting, 2023.
Proceedings, refereed
2023
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A. H. Z. Nik, M. Riegler, P. Halvorsen and A. Storås

Generation of Synthetic Tabular Healthcare Data Using Generative Adversarial Networks

In International conference on multimedia modeling. Springer International Publishing, 2023.
Proceedings, refereed
2023
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A. Storås, F. Fineide, H. L. Hammer, A. Khan, M. Magnø, C. Xiangjung, P. Halvorsen, T. Utheim and M. Riegler

Using explainable artificial intelligence (XAI) to explore factors affecting meibomian gland (MG) dropout

In ARVO Annual Meeting, 2023.
Proceedings, refereed
2023
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2023

Journal articles

A. Storås, O. E. Andersen, S. Lockhart, R. Thielemann, F. Gnesin, V. Thambawita, S. Hicks, J. Kanters, I. Strümke, P. Halvorsen et al.

Usefulness of Heat Map Explanations for Deep-Learning-Based Electrocardiogram Analysis

Diagnostics 13, no. 14 (2023).
Status: Published

Proceedings, refereed

F. Fineide, A. Storås, M. Magnø, H. L. Hammer, X. Chen, A. Khan, P. Halvorsen, T. Utheim and M. Riegler

Predicting the degree of meibomian gland dropout with artificial intelligence

In ARVO Annual Meeting, 2023.
Status: Published
T. Nguyen, A. Storås, V. Thambawita, S. Hicks, P. Halvorsen and M. Riegler

Multimedia datasets: challenges and future possibilities

In International conference on multimedia modeling, 2023.
Status: Published
A. H. Z. Nik, M. Riegler, P. Halvorsen and A. Storås

Generation of Synthetic Tabular Healthcare Data Using Generative Adversarial Networks

In International conference on multimedia modeling. Springer International Publishing, 2023.
Status: Published
A. Storås, F. Fineide, H. L. Hammer, A. Khan, M. Magnø, C. Xiangjung, P. Halvorsen, T. Utheim and M. Riegler

Using explainable artificial intelligence (XAI) to explore factors affecting meibomian gland (MG) dropout

In ARVO Annual Meeting, 2023.
Status: Published
2022

Journal articles

F. Fineide, A. Storås, X. Chen, M. S. Magnø, A. Yazidi, M. Riegler and T. P. Utheim

Predicting an unstable tear film through artificial intelligence

Scientific Reports 12, no. 1 (2022): 21416.
Status: Published
S. Hicks, V. Thambawita, A. Storås, T. B. Haugen, H. L. Hammer, P. Halvorsen, M. Riegler and M. H. Stensen

Automatic Tracking of the ICSI procedure using Deep Learning

Human Reproduction 37, no. Supplement_1 (2022).
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
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
V. Thambawita, S. Hicks, A. Storås, O. Witczak, J. M. Andersen, H. L. Hammer, P. Halvorsen, M. Riegler and H. B. Trine

Real-time deep learning based multi object tracking of spermatozoa in fresh samples

Human Reproduction 37, no. Supplement_1, July 2022, deac107.104 (2022).
Status: Published