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
Work
Year: 2022
Type: article
Abstract: This article's main contributions are twofold: 1) to demonstrate how to apply the general European Union's High-Level Expert Group's (EU HLEG) guidelines for trustworthy AI in practice for the domain ... more
Authors Himanshi Allahabadi, Julia Amann, Isabelle Balot, Andrea Beretta, Charles E. Binkley +52 more
Institutions ETH Zurich, Diplomatique, Istituto di Scienza e Tecnologie dell'Informazione "Alessandro Faedo", National Research Council, Hackensack Meridian Health +48 more
Cites: 33
Cited by: 24
Related to: 10
FWCI: 4.797
Citation percentile (by year/subfield): 99.99
Topic: COVID-19 diagnosis using AI
Subfield: Radiology, Nuclear Medicine and Imaging
Field: Medicine
Domain: Health Sciences
Sustainable Development Goal Good health and well-being
Open Access status: hybrid