output
20222025
most citedMultimodal Explainability via Latent Shift applied to COVID-19 stratification

30 citations

researchers with a paper here

Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.

collaborating institutions

3 papers

cs.AI2025★ 5 cited

XGeM: A Multi-Prompt Foundation Model for Multimodal Medical Data Generation

Daniele Molino, Francesco Di Feola, Eliodoro Faiella +5

The adoption of Artificial Intelligence in medical imaging holds great promise, yet it remains hindered by challenges such as data scarcity, privacy concerns, and the need for robu…

cs.LG2024★ 3 cited

When Can You Trust Your Explanations? A Robustness Analysis on Feature Importances

Ilaria Vascotto, Alex Rodriguez, Alessandro Bonaita +1

Recent legislative regulations have underlined the need for accountable and transparent artificial intelligence systems and have contributed to a growing interest in the Explainabl…

cs.AI2022★ 30 cited

Multimodal Explainability via Latent Shift applied to COVID-19 stratification

Valerio Guarrasi, Lorenzo Tronchin, Domenico Albano +4

We are witnessing a widespread adoption of artificial intelligence in healthcare. However, most of the advancements in deep learning in this area consider only unimodal data, negle…