Article Versions Notes

Iori M, Di Castelnuovo C, Verzellesi L, Meglioli G, Lippolis DG, Nitrosi A, Monelli F, Besutti G, Trojani V, Bertolini M, et al. Mortality Prediction of COVID-19 Patients Using Radiomic and Neural Network Features Extracted from a Wide Chest X-ray Sample Size: A Robust Approach for Different Medical Imbalanced Scenarios. Applied Sciences. 2022; 12(8):3903. https://doi.org/10.3390/app12083903

Iori, Mauro, Carlo Di Castelnuovo, Laura Verzellesi, Greta Meglioli, Davide Giosuè Lippolis, Andrea Nitrosi, Filippo Monelli, Giulia Besutti, Valeria Trojani, Marco Bertolini, and et al. 2022. "Mortality Prediction of COVID-19 Patients Using Radiomic and Neural Network Features Extracted from a Wide Chest X-ray Sample Size: A Robust Approach for Different Medical Imbalanced Scenarios" Applied Sciences 12, no. 8: 3903. https://doi.org/10.3390/app12083903

Iori, M., Di Castelnuovo, C., Verzellesi, L., Meglioli, G., Lippolis, D. G., Nitrosi, A., Monelli, F., Besutti, G., Trojani, V., Bertolini, M., Botti, A., Castellani, G., Remondini, D., Sghedoni, R., Croci, S., & Salvarani, C. (2022). Mortality Prediction of COVID-19 Patients Using Radiomic and Neural Network Features Extracted from a Wide Chest X-ray Sample Size: A Robust Approach for Different Medical Imbalanced Scenarios. Applied Sciences, 12(8), 3903. https://doi.org/10.3390/app12083903