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COVID-19 Chest Computed Tomography to Stratify Severity and Disease Extension by Artificial Neural Network Computer-Aided Diagnosis
Purpose: This work aims to develop a computer-aided diagnosis (CAD) to quantify the extent of pulmonary involvement (PI) in COVID-19 as well as the radiological patterns referred to as lung opacities in chest computer tomography (CT). Methods: One hundred thirty subjects with COVID-19 pneumonia who...
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| Publicado no: | Front Med (Lausanne) |
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| Main Authors: | , , , , , , , , , , |
| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
Frontiers Media S.A.
2020
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| Assuntos: | |
| Acesso em linha: | https://ncbi.nlm.nih.gov/pmc/articles/PMC7746855/ https://ncbi.nlm.nih.gov/pubmed/33344471 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.3389/fmed.2020.577609 |
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