2 papers
cs.LG2026
A feature-stable and explainable machine learning framework for trustworthy decision-making under incomplete clinical data
Justyna Andrys-Olek, Paulina Tworek, Luca Gherardini +4
Machine learning models are increasingly applied to biomedical data, yet their adoption in high stakes domains remains limited by poor robustness, limited interpretability, and ins…
cs.LG2024
Preservation of Feature Stability in Machine Learning Under Data Uncertainty for Decision Support in Critical Domains
Karol CapaÅa, Paulina Tworek, Jose Sousa
In a world where Machine Learning (ML) is increasingly deployed to support decision-making in critical domains, providing decision-makers with explainable, stable, and relevant inp…