ORCID: https://orcid.org/0000-0002-4849-8034; Huemmer, Christian; Preuhs, Alexander; Buizza, Guiulia ORCID: https://orcid.org/0000-0001-5504-1262; Hoppe, Boj F. ORCID: https://orcid.org/0000-0001-6248-5128; Dinkel, Julien; Koliogiannis, Vanessa; Fink, Nicola; Goller, Sophia S. ORCID: https://orcid.org/0000-0002-0964-8386; Schwarze, Vincent; Mansour, Nabeel ORCID: https://orcid.org/0000-0002-3467-1916; Schmidt, Vanessa F. ORCID: https://orcid.org/0000-0002-7067-2203; Fischer, Maximilian ORCID: https://orcid.org/0000-0001-9172-3316; Jörgens, Maximilian ORCID: https://orcid.org/0000-0002-1877-7673; Ben Khaled, Najib ORCID: https://orcid.org/0000-0002-9681-2542; Liebig, Thomas; Ricke, Jens; Rueckel, Johannes und Sabel, Bastian O.
(2024):
Nonradiology health-care professionals significantly benefit from AI assistance in emergency-related chest radiography interpretation.
In: CHEST: pp. 1-12 [Forthcoming]
| Item Type: | Journal article |
|---|---|
| Faculties: | Medicine > Medical Center of the University of Munich Medicine > Medical Center of the University of Munich > Clinic and Polyclinic for Radiology |
| Subjects: | 600 Technology > 610 Medicine and health |
| ISSN: | 0012-3692 |
| Language: | English |
| Item ID: | 118389 |
| Date Deposited: | 08. Jul 2024 08:46 |
| Last Modified: | 12. Jul 2024 07:27 |
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