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Filters: Keyword is Explainable artificial intelligence  [Clear All Filters]
2023
A. Storås and J. Sundgaard. Concept Explanations for Deep Learning-Based Diabetic Retinopathy Diagnosis. Nordic AI Meet 2023, 2023.
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.
A. Storås and J. Sundgaard. Looking into Concept Explanation Methods for Diabetic Retinopathy Classification In Workshop on Interpretability of Machine Intelligence in Medical Image Computing at MICCAI 2023., 2023.
F. Fineide, A. Storås, M. Riegler and T. Utheim. Predicting Meibomian Gland Dropout and Feature Importance Analysis with Explainable Artificial Intelligence In IEEE International Symposium on Computer-Based Medical Systems (IEEE CBMS2023)., 2023.
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).
2022
A. Storås, I. Strümke, M. Riegler and P. Halvorsen. Explainable Artificial Intelligence in Medicine In Nordic AI Meet 2022., 2022.
A. Storås. Unsupervised Image Segmentation via Self-Supervised Learning Image Classification In MediaEval 2021. Working Notes Proceedings of the MediaEval 2021 Workshop ed. CEUR Workshop Proceedings, 2022.PDF icon workingnotesmedico2021andrearevised9december.pdf (1.1 MB)