Assessing Trustworthy AI in Times of COVID-19: Deep Learning for Predicting a Multiregional Score Conveying the Degree of Lung Compromise in COVID-19 PatientsHimanshi Allahabadi, Jesmin Jahan Tithi, Roberto V. Zicari et al.|IEEE Transactions on Technology and Society|2022Cited by 37
Lessons Learned from Assessing Trustworthy AI in PracticeDennis Vetter, Julia Amann, Frédérick Bruneault et al.|Digital Society|2023Cited by 28
How to Assess Trustworthy AI in PracticeRoberto V. Zicari, Renee Wurth, Julia Amann et al.|arXiv (Cornell University)|2022Cited by 10
Lessons Learned in Performing a Trustworthy AI and Fundamental Rights AssessmentMarjolein Boonstra, Roberto V. Zicari, Frédérick Bruneault et al.|arXiv (Cornell University)|2024Cited by 0
Co-design for Trustworthy AI: An Interpretable and Explainable Tool for Type 2 Diabetes Prediction Using Genomic Polygenic Risk ScoresRalf Beuthan, Roberto V. Zicari, Megan Coffee et al.|arXiv (Cornell University)|2026Cited by 0