3D Printing of CT Dataset: Validation of an Open Source and Consumer-Available Workflow. - Chandra Bortolotto; Esmeralda Eshja; Caterina Peroni; Matteo A. Orlandi; Nicola Bizzotto; Paolo Poggi (J. Digit. Imaging, 2016)

ALFABETO: Supporting COVID-19 Hospital Admissions with Bayesian Networks. - Giovanna Nicora; Antonio Lo Tito; Antonella Donatelli; Giovanni Callea; Carla Biasibetti; Maria Vittoria Galli; Federico Comotto; Chandra Bortolotto; Stefano Perlini; Lorenzo Preda; Riccardo Bellazzi (SMARTERCARE@AI*IA, 2021)

AIforCOVID: Predicting the clinical outcomes in patients with COVID-19 applying AI to chest-X-rays. An Italian multicentre study. - Paolo Soda; Natascha Claudia D'Amico; Jacopo Tessadori; Giovanni Valbusa; Valerio Guarrasi; Chandra Bortolotto; Muhammad Usman Akbar; Rosa Sicilia; Ermanno Cordelli; Deborah Fazzini; Michaela Cellina; Giancarlo Oliva; et al. (Medical Image Anal., 2021)

CATE (Coronary Artery Tortuosity Evaluator): A Semi-Automatic Tool for Quantitative Assessment of Coronary Artery Tortuosity from CT Angiography. - Michela Ferrari; Mario Urtis; Lorenzo Giuliani; Alice Lionetti; Chandra Bortolotto; Francesco Prati; Lorenzo Preda; Eloisa Arbustini; Giovanni Magenes (MeMeA, 2024)

Reshaping free-text radiology notes into structured reports with generative question answering transformers. - Laura Bergomi; Tommaso Mario Buonocore; Paolo Antonazzo; Lorenzo Alberghi; Riccardo Bellazzi; Lorenzo Preda; Chandra Bortolotto; Enea Parimbelli (Artif. Intell. Medicine, 2024)

Reshaping Free-Text Radiology Notes Into Structured Reports With Generative Transformers. - Laura Bergomi; Tommaso Mario Buonocore; Paolo Antonazzo; Lorenzo Alberghi; Riccardo Bellazzi; Lorenzo Preda; Chandra Bortolotto; Enea Parimbelli (CoRR, 2024)

Bayesian Networks in the Management of Hospital Admissions: A Comparison between Explainable AI and Black Box AI during the Pandemic. - Giovanna Nicora; Michele Catalano; Chandra Bortolotto; Marina Francesca Achilli; Gaia Messana; Antonio Lo Tito; Alessio Consonni; Sara Cutti; Federico Comotto; Giulia Maria Stella; Angelo Corsico; Stefano Perlini; et al. (J. Imaging, 2024)

Machine learning predicts pulmonary Long Covid sequelae using clinical data. - Ermanno Cordelli; Paolo Soda; Sara Citter; Elia Schiavon; Christian Salvatore; Deborah Fazzini; Greta Clementi; Michaela Cellina; Andrea Cozzi; Chandra Bortolotto; Lorenzo Preda; Luisa Francini; et al. (BMC Medical Informatics Decis. Mak., 2024)

Comparative clinical evaluation of "memory-efficient" synthetic 3d generative adversarial networks (gan) head-to-head to state of art: results on computed tomography of the chest. - Mahshid Shiri; Chandra Bortolotto; Alessandro Bruno; Alessio Consonni; Daniela Maria Grasso; Leonardo Brizzi; Daniele Loiacono; Lorenzo Preda (CoRR, 2025)

Which explanations do clinicians prefer? A comparative evaluation of XAI understandability and actionability in predicting the need for hospitalization. - Laura Bergomi; Giovanna Nicora; Marta Anna Orlowska; Chiara Podrecca; Riccardo Bellazzi; Caterina Fregosi; Francesco Salinaro; Marco Bonzano; Giuseppe Crescenzi; Francesco Speciale; Santi Di Pietro; Valentina Zuccaro; et al. (BMC Medical Informatics Decis. Mak., 2025)

Correction: Machine learning predicts pulmonary long Covid sequelae using clinical data. - Ermanno Cordelli; Paolo Soda; Sara Citter; Elia Schiavon; Christian Salvatore; Deborah Fazzini; Greta Clementi; Michaela Cellina; Andrea Cozzi; Chandra Bortolotto; Lorenzo Preda; Luisa Francini; et al. (BMC Medical Informatics Decis. Mak., 2025)