167 citations · 1k across the 73 of their papers we have counts for
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cs.AI2023★ 2 cited
Explaining and visualizing black-box models through counterfactual paths
Bastian Pfeifer, Mateusz Krzyzinski, Hubert Baniecki +3
Explainable AI (XAI) is an increasingly important area of machine learning research, which aims to make black-box models transparent and interpretable. In this paper, we propose a…
cs.AI2023
Prevention is better than cure: a case study of the abnormalities detection in the chest
Weronika Hryniewska, Piotr Czarnecki, Jakub Wiśniewski +2
Prevention is better than cure. This old truth applies not only to the prevention of diseases but also to the prevention of issues with AI models used in medicine. The source of ma…