- SurvSHAP(t): Time-dependent explanations of machine learning survival modelsarXiv:2208.11080v2, 2022
This work introduces the first time-dependent explanation for interpreting survival models.
- The Grammar of Interactive Explanatory Model AnalysisarXiv:2005.00497v4, 2022
- Multi-omics disease module detection with an explainable Greedy Decision ForestScientific Reports, 2022
- Quantitative analysis of RT-PCR test results for SARS-CoV-2 diagnostics across Poland during COVID-19 pandemic: Comparison between early stage and major pandemic waves in 2020 and 2021 with reference to SARS-CoV-2 variantsAdvances in Medical Sciences, 2022
- ECML PKDD
oralFooling Partial Dependence via Data PoisoningIn: European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD), 2022 This work is the core of our BSc thesis defended at Warsaw University of Technology in 2021.
posterManipulating SHAP via Adversarial Data Perturbations (Student Abstract)In: AAAI Conference on Artificial Intelligence (AAAI), 2022
- A Signature of 14 Long Non-Coding RNAs (lncRNAs) as a Step towards Precision Diagnosis for NSCLCCancers, 2022
posterResponsible Prediction Making of COVID-19 Mortality (Student Abstract)In: AAAI Conference on Artificial Intelligence (AAAI), 2021
- modelStudio: Interactive studio with explanations for ML predictive modelsJournal of Open Source Software, 2019