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interpret-time-to-event

This repository will contain supplementary code associated with the article

H. Baniecki, B. Sobieski, P. Szatkowski, P. Bombinski, P. Biecek. Interpretable machine learning for time-to-event prediction in medicine and healthcare. in review, 2024

Directory xlungs-trustworthy-los-prediction contains updated code and data from the repository https://github.com/mi2datalab/xlungs-trustworthy-los-prediction attached to the paper

H. Baniecki, B. Sobieski, P. Bombinski, P. Szatkowski, P. Biecek. Hospital Length of Stay Prediction Based on Multi-modal Data towards Trustworthy Human-AI Collaboration in Radiomics. International Conference on Artificial Intelligence in Medicine, 2023

Acknowledgements

This work was financially supported by the Polish National Center for Research and Development grant number INFOSTRATEG-I/0022/2021-00, and carried out with the support of the Laboratory of Bioinformatics and Computational Genomics and the High Performance Computing Center of the Faculty of Mathematics and Information Science, Warsaw University of Technology.