Search Results for author: Deborah Fazzini

Found 2 papers, 1 papers with code

Multimodal Explainability via Latent Shift applied to COVID-19 stratification

no code implementations • 28 Dec 2022 • Valerio Guarrasi, Lorenzo Tronchin, Domenico Albano, Eliodoro Faiella, Deborah Fazzini, Domiziana Santucci, Paolo Soda

The explanation of the decision taken is computed by applying a latent shift that, simulates a counterfactual prediction revealing the features of each modality that contribute the most to the decision and a quantitative score indicating the modality importance.

counterfactual

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AIforCOVID: predicting the clinical outcomes in patients with COVID-19 applying AI to chest-X-rays. An Italian multicentre study

1 code implementation • 11 Dec 2020 • 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, Gian Paolo Carrafiello, Giulia Castorani, Annalisa Simeone, Lorenzo Preda, Giulio Iannello, Alessio Del Bue, Fabio Tedoldi, Marco Alì, Diego Sona, Sergio Papa

Exhaustive evaluation shows promising performance both in 10-fold and leave-one-centre-out cross-validation, implying that clinical data and images have the potential to provide useful information for the management of patients and hospital resources.

Computed Tomography (CT) Management

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