Do not repeat these mistakes - a critical appraisal of applications of explainable artificial intelligence for image based COVID-19 detection. - Weronika Hryniewska; Przemyslaw Bombinski; Patryk Szatkowski; Paulina Tomaszewska; Artur Przelaskowski; Przemyslaw Biecek (CoRR, 2020)

Checklist for responsible deep learning modeling of medical images based on COVID-19 detection studies. - Weronika Hryniewska; Przemyslaw Bombinski; Patryk Szatkowski; Paulina Tomaszewska; Artur Przelaskowski; Przemyslaw Biecek (Pattern Recognit., 2021)

Challenges facing the explainability of age prediction models: case study for two modalities. - Mikolaj Spytek; Weronika Hryniewska-Guzik; Jaroslaw Zygierewicz; Jacek Rogala; Przemyslaw Biecek (CoRR, 2023)

Prevention is better than cure: a case study of the abnormalities detection in the chest. - Weronika Hryniewska; Piotr Czarnecki; Jakub Wisniewski; Przemyslaw Bombinski; Przemyslaw Biecek (CoRR, 2023)

Multi-task learning for classification, segmentation, reconstruction, and detection on chest CT scans. - Weronika Hryniewska-Guzik; Maria Kedzierska; Przemyslaw Biecek (CoRR, 2023)

CNN-Based Explanation Ensembling for Dataset, Representation and Explanations Evaluation. - Weronika Hryniewska-Guzik; Luca Longo; Przemyslaw Biecek (xAI (2), 2024)

NormEnsembleXAI: Unveiling the Strengths and Weaknesses of XAI Ensemble Techniques. - Weronika Hryniewska-Guzik; Bartosz Sawicki; Przemyslaw Biecek (CoRR, 2024)

A comparative analysis of deep learning models for lung segmentation on X-ray images. - Weronika Hryniewska-Guzik; Jakub Bilski; Bartosz Chrostowski; Jakub Drak Sbahi; Przemyslaw Biecek (CoRR, 2024)

LIMEcraft: handcrafted superpixel selection and inspection for Visual eXplanations. - Weronika Hryniewska; Adrianna Grudzien; Przemyslaw Biecek (Mach. Learn., 2024)

X-ray transferable polyrepresentation learning. - Weronika Hryniewska-Guzik; Przemyslaw Biecek (CoRR, 2025)