Hallazgos por imágenes en COVID-19: actualización y guía práctica

Díaz, Facundo N; Castro, Horacio M; Mestas Núñez, Marcos; Maritano Furcada, Joaquín; Dulcich, Gonzalo; Beresñak, Alejandro D; Ocantos, Jorge A; Seehaus, Alberto.
Rev. Hosp. Ital. B. Aires (2004) ; 40(3): 144-150, sept. 2020. ilus, tab
Artículo en Español | LILACS | ID: biblio-1129376

Documentos relacionados

  1. DDA-SSNets: Dual decoder attention-based semantic segmentation networks for COVID-19 infection segmentation and classification using chest X-Ray images.
  2. Canadian Society of Thoracic Radiology/Canadian Association of Radiologists Consensus Statement Regarding Chest Imaging in Suspected and Confirmed COVID-19.
  3. Clinical characteristics and chest CT imaging features of critically ill COVID-19 patients.
  4. Time Course of Lung Changes at Chest CT during Recovery from Coronavirus Disease 2019 (COVID-19).
  5. [Identifying Novel Coronavirus Pneumonia With CT Images: A Deep Learning Approach With Detail Upsampling and Attention Guidance].
  6. COVID-19 in pediatric patients: a case series from the Bronx, NY.
  7. CT findings of 144 in-hospital patients with influenza pneumonia: A retrospective analysis.
  8. The Canadian Association for Interventional Radiology (CAIR) and Canadian Association of Radiologists (CAR) Guidelines for Interventional Radiology Procedures for Patients With Suspected or Confirmed COVID-19.
  9. Lung involvement in macrophage activation syndrome and severe COVID-19: results from a cross-sectional study to assess clinical, laboratory and artificial intelligence-radiological differences.
  10. Radiographic findings in 240 patients with COVID-19 pneumonia: time-dependence after the onset of symptoms.