Lorenzo Preda

According to our database, Lorenzo Preda authored at least 7 papers between 2021 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

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, Matteo Tortora, Isabella Castiglioni, Sergio Papa, Diego Sona, Marco Alì

BMC Medical Informatics Decis. Mak., December, 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, Riccardo Bellazzi, Raffaele Bruno, Lorenzo Preda

J. Imaging, May, 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

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

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

Proceedings of the IEEE International Symposium on Medical Measurements and Applications, 2024

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, Giovanni Callea, Silvia Panella, Maurizio Cariati, Diletta Cozzi, Vittorio Miele, Elvira Stellato, Gianpaolo Carrafiello, Giulia Castorani, Annalisa Simeone, Lorenzo Preda, Giulio Iannello, Alessio Del Bue, Fabio Tedoldi, Marco Alì, Diego Sona, Sergio Papa

Medical Image Anal., 2021

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

Proceedings of the Workshop on Towards Smarter Health Care: Can Artificial Intelligence Help? co-located with 20th International Conference of the Italian Association for Artificial Intelligence (AIxIA2021), 2021