CERNIGLIARO, FRANCO
CERNIGLIARO, FRANCO
Universita' degli Studi di MILANO
Artificial intelligence-assisted quantification of COVID-19 pneumonia burden from computed tomography improves prediction of adverse outcomes over visual scoring systems
2023 K. Grodecki, A. Killekar, J. Simon, A. Lin, S. Cadet, P. Mcelhinney, C. Chan, M.C. Williams, B.D. Pressman, P. Julien, D. Li, P. Chen, N. Gaibazzi, U. Thakur, E. Mancini, C. Agalbato, J. Munechika, H. Matsumoto, R. Menè, G. Parati, F. Cernigliaro, N. Nerlekar, C. Torlasco, G. Pontone, P. Maurovich-Horvat, P.J. Slomka, D. Dey
Rapid quantification of COVID-19 pneumonia burden from computed tomography with convolutional long short-term memory networks
2022 A. Killekar, K. Grodecki, A. Lin, S. Cadet, P. Mcelhinney, A. Razipour, C. Chan, B.D. Pressman, P. Julien, P. Chen, J. Simon, P. Maurovich-Horvat, N. Gaibazzi, U. Thakur, E. Mancini, C. Agalbato, J. Munechika, H. Matsumoto, R. Menè, G. Parati, F. Cernigliaro, N. Nerlekar, C. Torlasco, G. Pontone, D. Dey, P. Slomka
Rapid quantification of COVID-19 pneumonia burden from computed tomography with convolutional LSTM networks
2021 K. Grodecki, A. Killekar, A. Lin, S. Cadet, P. Mcelhinney, A. Razipour, C. Chan, B.D. Pressman, P. Julien, J. Simon, P. Maurovich-Horvat, N. Gaibazzi, U. Thakur, E. Mancini, C. Agalbato, J. Munechika, H. Matsumoto, R. Menè, G. Parati, F. Cernigliaro, N. Nerlekar, C. Torlasco, G. Pontone, D. Dey, P.J. Slomka
Contrast-enhanced ultrasonography in the follow-up of patients with hepatic metastases from breast carcinoma
2007 P. Della Vigna, F. Cernigliaro, L. Monfardini, S. Gandini, M. Bellomi