2 papers
cs.LG2026
Explainable AI for Cancer Drug Response Prediction: Beyond Univariate Feature Attributions
Martino Ciaperoni, Margherita Lalli, Simone Piaggesi +6
Predicting cancer drug response from transcriptomic profiles is a cornerstone of precision oncology, yet the scientific value of machine learning models hinges not solely on predic…
cs.LG2023
Interpretability from a new lens: Integrating Stratification and Domain knowledge for Biomedical Applications
Anthony Onoja, Francesco Raimondi
The use of machine learning (ML) techniques in the biomedical field has become increasingly important, particularly with the large amounts of data generated by the aftermath of the…