Data Models for an Imaging Bio-bank for Colorectal, Prostate and Gastric Cancer: the NAVIGATOR Project. - Andrea Berti; Gianluca Carloni; Sara Colantonio; Maria Antonietta Pascali; Paolo Manghi; Pasquale Pagano; Rossana Buongiorno; Eva Pachetti; Claudia Caudai; Domenico Di Gangi; Emanuele Carlini; Zeno Falaschi; et al. (BHI, 2022)

On the Effectiveness of 3D Vision Transformers for the Prediction of Prostate Cancer Aggressiveness. - Eva Pachetti; Sara Colantonio; Maria Antonietta Pascali (ICIAP Workshops, 2022)

Causality-Driven One-Shot Learning for Prostate Cancer Grading from MRI. - Gianluca Carloni; Eva Pachetti; Sara Colantonio (ICCV (Workshops), 2023)

Exploring the potentials and challenges of Artificial Intelligence in supporting clinical diagnostics and remote assistance for the health and well-being of individuals. - Andrea Berti; Rossana Buongiorno; Gianluca Carloni; Claudia Caudai; Giulio Del Corso; Danila Germanese; Eva Pachetti; Maria Antonietta Pascali; Sara Colantonio (Ital-IA, 2023)

Cine Cardiac MRI Reconstruction Using a Convolutional Recurrent Network with Refinement. - Yuyang Xue; Yuning Du; Gianluca Carloni; Eva Pachetti; Connor Jordan; Sotirios A. Tsaftaris (STACOM@MICCAI, 2023)

Radiomics-Based Reliable Predictions of Side Effects After Radiotherapy for Prostate Cancer. - Giulio Del Corso; Eva Pachetti; Rossana Buongiorno; Ana Carolina Rodrigues; Danila Germanese; Maria Antonietta Pascali; José G. de Almeida; Nuno Miguel Rodrigues; Manolis Tsiknakis; Nickolas Papanikolaou 003; Daniele Regge; Kostas Marias; et al. (ISBI, 2024)

From Covid-19 detection to cancer grading: how medical-AI is boosting clinical diagnostics and may improve treatment. - Andrea Berti; Rossana Buongiorno; Gianluca Carloni; Claudia Caudai; Francesco Conti 004; Giulio Del Corso; Danila Germanese; Davide Moroni; Eva Pachetti; Maria Antonietta Pascali; Sara Colantonio (Ital-IA, 2024)

Seeing More with Less: Meta-learning and Diffusion Models for Tumor Characterization in Low-Data Settings. - Eva Pachetti; Sara Colantonio (CaPTion@MICCAI, 2024)

Data and System Traceability for Transparent AI in Medical Imaging. - Sara Colantonio; Andrea Berti; Gianluca Carloni; Claudia Caudai; Giulio Del Corso; Danila Germanese; Eva Pachetti; Maria Antonietta Pascali; Varvara Kalokyri; Haridimos Kondylakis; Charalampos Kalantzopoulos; Nikolaos S. Tachos; et al. (SEBD, 2024)

A systematic review of few-shot learning in medical imaging. - Eva Pachetti; Sara Colantonio (Artif. Intell. Medicine, 2024)

Boosting Few-Shot Learning with Disentangled Self-Supervised Learning and Meta-Learning for Medical Image Classification. - Eva Pachetti; Sotirios A. Tsaftaris; Sara Colantonio (CoRR, 2024)

Few-Shot Conditional Learning: Automatic and Reliable Device Classification for Medical Test Equipment. - Eva Pachetti; Giulio Del Corso; Serena Bardelli; Sara Colantonio (J. Imaging, 2024)