| SurvSHAP(t): Time-dependent explanations of machine learning survival models M Krzyziński, M Spytek, H Baniecki, P Biecek Knowledge-Based Systems 262, 110234, 2023 | 46 | 2023 |
| Machine learning models demonstrate that clinicopathologic variables are comparable to gene expression prognostic signature in predicting survival in uveal melanoma P Donizy, M Krzyzinski, A Markiewicz, P Karpinski, K Kotowski, A Kowalik, ... European Journal of Cancer 174, 251-260, 2022 | 10 | 2022 |
| Amelanotic Uveal Melanomas Evaluated by Indirect Ophthalmoscopy Reveal Better Long-Term Prognosis Than Pigmented Primary Tumours—A Single Centre Experience A Markiewicz, P Donizy, M Nowak, M Krzyziński, M Elas, PM Płonka, ... Cancers 14 (11), 2753, 2022 | 10 | 2022 |
| Coloring squares of planar graphs with small maximum degree M Krzyziński, P Rzążewski, S Tur Discussiones Mathematicae Graph Theory, 2022 | 5 | 2022 |
| Performance is not enough: the story told by a Rashomon quartet P Biecek, H Baniecki, M Krzyziński, D Cook Journal of Computational and Graphical Statistics, 1-6, 2024 | 4* | 2024 |
| Exploration of the Rashomon Set Assists Trustworthy Explanations for Medical Data K Kobylińska, M Krzyziński, R Machowicz, M Adamek, P Biecek arXiv e-prints, arXiv: 2308.11446, 2023 | 4* | 2023 |
| survex: an R package for explaining machine learning survival models M Spytek, M Krzyziński, SH Langbein, H Baniecki, MN Wright, P Biecek Bioinformatics 39 (12), btad723, 2023 | 3 | 2023 |
| Climate Policy Tracker: Pipeline for automated analysis of public climate policies A Żółkowski, M Krzyziński, P Wilczyński, S Giziński, E Wiśnios, B Pieliński, ... NeurIPS 2022 Workshop: Tackling Climate Change with Machine Learning, 2022 | 3 | 2022 |
| Ki67 is a better marker than PRAME in risk stratification of BAP1-positive and BAP1-loss uveal melanomas P Donizy, M Spytek, M Krzyziński, K Kotowski, A Markiewicz, ... British Journal of Ophthalmology 108 (7), 1005-1010, 2024 | 1 | 2024 |
| Interpretable machine learning for survival analysis SH Langbein, M Krzyziński, M Spytek, H Baniecki, P Biecek, MN Wright arXiv preprint arXiv:2403.10250, 2024 | 1 | 2024 |
| Explaining and visualizing black-box models through counterfactual paths B Pfeifer, M Krzyzinski, H Baniecki, A Saranti, A Holzinger, P Biecek arXiv preprint arXiv:2307.07764, 2023 | 1* | 2023 |
| A novel radiomics approach for predicting TACE outcomes in hepatocellular carcinoma patients using deep learning for multi-organ segmentation K Bartnik, M Krzyziński, T Bartczak, K Korzeniowski, K Lamparski, ... Scientific Reports 14 (1), 14779, 2024 | | 2024 |
| Mining United Nations General Assembly Debates M Grzyb, M Krzyziński, B Sobieski, M Spytek, B Pieliński, D Dan, ... arXiv preprint arXiv:2406.13553, 2024 | | 2024 |
| SATB2, CKAE1/AE3, and synaptophysin as a sensitive immunohistochemical panel for the detection of lymph node metastases of Merkel cell carcinoma A Szumera-Cieckiewicz, D Massi, A Cassisa, M Krzyzinski, ... Virchows Archiv 484 (4), 629-636, 2024 | | 2024 |
| HADES: Homologous Automated Document Exploration and Summarization P Wilczyński, A Żółkowski, M Krzyziński, E Wiśnios, B Pieliński, S Giziński, ... arXiv preprint arXiv:2302.13099, 2023 | | 2023 |
| Prognostic Role of Concomitant BAP1 and PRAME Expression in Uveal Melanomas P Donizy, KW Kotowski, A Markiewicz, M Krzyzinski, P Biecek, ... | | 2023 |
