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.LG2025
CACTUS as a Reliable Tool for Early Classification of Age-related Macular Degeneration
Luca Gherardini, Imre Lengyel, Tunde Peto +6
Machine Learning (ML) is used to tackle various tasks, such as disease classification and prediction. The effectiveness of ML models relies heavily on having large amounts of compl…