학술논문
Assessing Trustworthy AI in Times of COVID-19: Deep Learning for Predicting a Multiregional Score Conveying the Degree of Lung Compromise in COVID-19 Patients
Document Type
Artikel
Author
Allahabadi, H; Amann, J; Balot, I; Beretta, A; Binkley, C; Bozenhard, J; Bruneault, F; Brusseau, J; Candemir, S; Cappellini, LA; Chakraborty, S; Cherciu, N; Cociancig, C; Coffee, M; Ek, I; Espinosa-Leal, L; Farina, D; Fieux-Castagnet, G; Frauenfelder, T; Gallucci, A; Giuliani, G; Golda, A; van Halem, I; Hildt, E; Holm, S; Kararigas, G; Krier, SA; Kuhne, U; Lizzi, F; Madai, VI; Markus, AF; Masis, S; Mathez, EW; Mureddu, F; Neri, E; Osika, W; Ozols, M; Panigutti, C; Parent, B; Pratesi, F; Moreno-Sanchez, PA; Sartor, G; Savardi, M; Signoroni, A; Sormunen, HM; Spezzatti, A; Srivastava, A; Stephansen, AF; Theng, LB; Tithi, JJ; Tuominen, J; Umbrello, S; Vaccher, F; Vetter, D; Westerlund, M; Wurth, R; Zicari, RV
Source
IEEE transactions on technology and society. 3(4):272-289
Subject
Language
English
English
English
ISSN
2637-6415