Making AI trustworthy in multimodal and healthcare scenarios. - Ermanno Cordelli; Valerio Guarrasi; Giulio Iannello; Filippo Ruffini; Rosa Sicilia; Paolo Soda; Lorenzo Tronchin (Ital-IA, 2023)

Towards AI-driven Next Generation Personalized Healthcare and Well-being. - Fatih Aksu; Alessandro Bria; Alice Natalina Caragliano; Camillo Maria Caruso; Wenting Chen; Ermanno Cordelli; Omar Coser; Arianna Francesconi; Leonardo Furia; Valerio Guarrasi; Giulio Iannello; Clemente Lauretti; et al. (Ital-IA, 2024)

Multi-Dataset Multi-Task Learning for COVID-19 Prognosis. - Filippo Ruffini; Lorenzo Tronchin; Zhuoru Wu; Wenting Chen; Paolo Soda; Linlin Shen; Valerio Guarrasi (MICCAI (12), 2024)

Doctor-in-the-Loop: An explainable, multi-view deep learning framework for predicting pathological response in non-small cell lung cancer. - Alice Natalina Caragliano; Filippo Ruffini; Carlo Greco; Edy Ippolito; Michele Fiore; Claudia Tacconi; Lorenzo Nibid; Giuseppe Perrone; Sara Ramella; Paolo Soda; Valerio Guarrasi (Image Vis. Comput., 2025)

A systematic review of intermediate fusion in multimodal deep learning for biomedical applications. - Valerio Guarrasi; Fatih Aksu; Camillo Maria Caruso; Francesco Di Feola; Aurora Rofena; Filippo Ruffini; Paolo Soda (Image Vis. Comput., 2025)

Text-to-CT Generation via 3D Latent Diffusion Model with Contrastive Vision-Language Pretraining. - Daniele Molino; Camillo Maria Caruso; Filippo Ruffini; Paolo Soda; Valerio Guarrasi (CoRR, 2025)

Benchmarking Foundation Models and Parameter-Efficient Fine-Tuning for Prognosis Prediction in Medical Imaging. - Filippo Ruffini; Elena Mulero Ayllon; Linlin Shen; Paolo Soda; Valerio Guarrasi (CoRR, 2025)