Przemyslaw Biecek
Orcid: 0000-0001-8423-1823Affiliations:
- Warsaw University of Technology, Poland
According to our database1,
Przemyslaw Biecek
authored at least 116 papers
between 2007 and 2025.
Collaborative distances:
Collaborative distances:
Timeline
Legend:
Book In proceedings Article PhD thesis Dataset OtherLinks
Online presence:
On csauthors.net:
Bibliography
2025
Interpretable machine learning for time-to-event prediction in medicine and healthcare.
Artif. Intell. Medicine, 2025
2024
Correction: AI content detection in the emerging information ecosystem: new obligations for media and tech companies.
Ethics Inf. Technol., December, 2024
AI content detection in the emerging information ecosystem: new obligations for media and tech companies.
Ethics Inf. Technol., December, 2024
IEEE J. Biomed. Health Informatics, November, 2024
Data Min. Knowl. Discov., September, 2024
Consolidated learning: a domain-specific model-free optimization strategy with validation on metaMIMIC benchmarks.
Mach. Learn., July, 2024
Mach. Learn., May, 2024
Big Tech influence over AI research revisited: Memetic analysis of attribution of ideas to affiliation.
J. Informetrics, 2024
Inf. Fusion, 2024
CoRR, 2024
CoRR, 2024
An Experimental Study on the Rashomon Effect of Balancing Methods in Imbalanced Classification.
CoRR, 2024
A comparative analysis of deep learning models for lung segmentation on X-ray images.
CoRR, 2024
Underestimation of lung regions on chest X-ray segmentation masks assessed by comparison with total lung volume evaluated on computed tomography.
CoRR, 2024
CoRR, 2024
CoRR, 2024
Antibody selection strategies and their impact in predicting clinical malaria based on multi-sera data.
BioData Min., 2024
CNN-Based Explanation Ensembling for Dataset, Representation and Explanations Evaluation.
Proceedings of the Explainable Artificial Intelligence, 2024
SRFAMap: A Method for Mapping Integrated Gradients of a CNN Trained with Statistical Radiomic Features to Medical Image Saliency Maps.
Proceedings of the Explainable Artificial Intelligence, 2024
Towards a crowdsourced framework for online hate speech moderation - a case study in the Indian political scenario.
Proceedings of the Companion Publication of the 16th ACM Web Science Conference, 2024
Proceedings of the Machine Learning and Knowledge Discovery in Databases. Research Track, 2024
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2024, 2024
Proceedings of the Forty-first International Conference on Machine Learning, 2024
Proceedings of the Forty-first International Conference on Machine Learning, 2024
Proceedings of the Computer Vision - ECCV 2024, 2024
Proceedings of the ECAI 2024 - 27th European Conference on Artificial Intelligence, 19-24 October 2024, Santiago de Compostela, Spain, 2024
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024
2023
Generative AI models should include detection mechanisms as a condition for public release.
Ethics Inf. Technol., December, 2023
Bioinform., December, 2023
Knowl. Based Syst., February, 2023
Multi-task learning for classification, segmentation, reconstruction, and detection on chest CT scans.
CoRR, 2023
Prevention is better than cure: a case study of the abnormalities detection in the chest.
CoRR, 2023
Challenges facing the explainability of age prediction models: case study for two modalities.
CoRR, 2023
The Effect of Balancing Methods on Model Behavior in Imbalanced Classification Problems.
Proceedings of the Fifth International Workshop on Learning with Imbalanced Domains: Theory and Applications, 2023
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023
Hospital Length of Stay Prediction Based on Multi-modal Data Towards Trustworthy Human-AI Collaboration in Radiomics.
Proceedings of the Artificial Intelligence in Medicine, 2023
2022
fairmodels: a Flexible Tool for Bias Detection, Visualization, and Mitigation in Binary Classification Models.
R J., 2022
Transparency, auditability, and explainability of machine learning models in credit scoring.
J. Oper. Res. Soc., 2022
CoRR, 2022
Performance, Opaqueness, Consequences, and Assumptions: Simple questions for responsible planning of machine learning solutions.
CoRR, 2022
Consolidated learning - a domain-specific model-free optimization strategy with examples for XGBoost and MIMIC-IV.
CoRR, 2022
A robust framework to investigate the reliability and stability of explainable artificial intelligence markers of Mild Cognitive Impairment and Alzheimer's Disease.
Brain Informatics, 2022
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2022
Proceedings of the ECML/PKDD Workshop on Meta-Knowledge Transfer, 2022
Proceedings of the 9th IEEE International Conference on Data Science and Advanced Analytics, 2022
Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022
2021
Checklist for responsible deep learning modeling of medical images based on COVID-19 detection studies.
Pattern Recognit., 2021
dalex: Responsible Machine Learning with Interactive Explainability and Fairness in Python.
J. Mach. Learn. Res., 2021
J. Intell. Inf. Syst., 2021
Simpler is better: Lifting interpretability-performance trade-off via automated feature engineering.
Decis. Support Syst., 2021
MAIR: Framework for mining relationships between research articles, strategies, and regulations in the field of explainable artificial intelligence.
CoRR, 2021
CoRR, 2021
Enabling Machine Learning Algorithms for Credit Scoring - Explainable Artificial Intelligence (XAI) methods for clear understanding complex predictive models.
CoRR, 2021
Triplot: model agnostic measures and visualisations for variable importance in predictive models that take into account the hierarchical correlation structure.
CoRR, 2021
CoRR, 2021
Proceedings of the Machine Learning and Principles and Practice of Knowledge Discovery in Databases, 2021
Proceedings of the MEDINFO 2021: One World, One Health - Global Partnership for Digital Innovation, 2021
Proceedings of the Neural Information Processing - 28th International Conference, 2021
Kleister: Key Information Extraction Datasets Involving Long Documents with Complex Layouts.
Proceedings of the 16th International Conference on Document Analysis and Recognition, 2021
Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021
2020
Do not repeat these mistakes - a critical appraisal of applications of explainable artificial intelligence for image based COVID-19 detection.
CoRR, 2020
MementoML: Performance of selected machine learning algorithm configurations on OpenML100 datasets.
CoRR, 2020
Kleister: A novel task for Information Extraction involving Long Documents with Complex Layout.
CoRR, 2020
CoRR, 2020
KRAB ZNF explorer - the online tool for the exploration of the transcriptomic profiles of KRAB-ZNF factors in The Cancer Genome Atlas.
Bioinform., 2020
What Would You Ask the Machine Learning Model? Identification of User Needs for Model Explanations Based on Human-Model Conversations.
Proceedings of the ECML PKDD 2020 Workshops, 2020
Proceedings of the xxAI - Beyond Explainable AI, 2020
2019
R J., 2019
modelDown: automated website generator with interpretable documentation for predictive machine learning models.
J. Open Source Softw., 2019
pyCeterisParibus: explaining Machine Learning models with Ceteris Paribus Profiles in Python.
J. Open Source Softw., 2019
J. Open Source Softw., 2019
CoRR, 2019
Proceedings of the Neural Information Processing - 26th International Conference, 2019
Proceedings of the 23rd Conference on Computational Natural Language Learning, 2019
Explainable Machine Learning for Modeling of Early Postoperative Mortality in Lung Cancer.
Proceedings of the Artificial Intelligence in Medicine: Knowledge Representation and Transparent and Explainable Systems, 2019
2018
J. Open Source Softw., 2018
Are you tough enough? Framework for Robustness Validation of Machine Comprehension Systems.
CoRR, 2018
CoRR, 2018
Does it care what you asked? Understanding Importance of Verbs in Deep Learning QA System.
Proceedings of the Workshop: Analyzing and Interpreting Neural Networks for NLP, 2018
Proceedings of the Workshop: Analyzing and Interpreting Neural Networks for NLP, 2018
2017
Merge and Select: Visualization of a likelihood based k-sample adaptive fusing and model selection.
CoRR, 2017
2011
Bi-Billboard: Symmetrization and Careful Choice of Informant Species Results in Higher Accuracy of Regulatory Element Prediction.
J. Comput. Biol., 2011
Deregulation upon DNA damage revealed by joint analysis of context-specific perturbation data.
BMC Bioinform., 2011
2010
2008
Optimisation of Asymmetric Mutational Pressure and Selection Pressure Around the Universal Genetic Code.
Proceedings of the Computational Science, 2008
2007
The role of intragenomic recombination rate in the evolution of population's genetic pool.
Theory Biosci., 2007
Comput. Stat. Data Anal., 2007