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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.
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. Allahabadi H, et al. Among authors: bozenhard j. IEEE Trans Technol Soc. 2022 Jul 29;3(4):272-289. doi: 10.1109/TTS.2022.3195114. eCollection 2022 Dec. IEEE Trans Technol Soc. 2022. PMID: 36573115 Free PMC article.