Quantification of COVID-19 Opacities on Chest CT – Evaluation of a Fully Automatic AI-approach to Noninvasively Differentiate Critical Versus Noncritical Patients

OBJECTIVES: To evaluate the potential of a fully automatic artificial intelligence (AI)-driven computed tomography (CT) software prototype to quantify severity of COVID-19 infection on chest CT in relationship with clinical and laboratory data. METHODS: We retrospectively analyzed 50 patients with l...

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Detalles Bibliográficos
Autores principales: Mader, Christoph, Bernatz, Simon, Michalik, Sabine, Koch, Vitali, Martin, Simon S., Mahmoudi, Scherwin, Basten, Lajos, Grünewald, Leon D., Bucher, Andreas, Albrecht, Moritz H., Vogl, Thomas J., Booz, Christian
Formato: Online Artículo Texto
Lenguaje:English
Publicado: The Association of University Radiologists. Published by Elsevier Inc. 2021
Materias:
Original Investigation
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7936551/
https://www.ncbi.nlm.nih.gov/pubmed/33741210
http://dx.doi.org/10.1016/j.acra.2021.03.001

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7936551/
https://www.ncbi.nlm.nih.gov/pubmed/33741210
http://dx.doi.org/10.1016/j.acra.2021.03.001

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