Thoracic imaging tests for the diagnosis of COVID‐19
Background The respiratory illness caused by SARS‐CoV‐2 infection continues to present
diagnostic challenges. Our 2020 edition of this review showed thoracic (chest) imaging to be …
diagnostic challenges. Our 2020 edition of this review showed thoracic (chest) imaging to be …
[HTML][HTML] Thoracic imaging tests for the diagnosis of COVID‐19
Background Our March 2021 edition of this review showed thoracic imaging computed
tomography (CT) to be sensitive and moderately specific in diagnosing COVID‐19 …
tomography (CT) to be sensitive and moderately specific in diagnosing COVID‐19 …
[HTML][HTML] Integrating deep learning CT-scan model, biological and clinical variables to predict severity of COVID-19 patients
N Lassau, S Ammari, E Chouzenoux, H Gortais… - Nature …, 2021 - nature.com
The SARS-COV-2 pandemic has put pressure on intensive care units, so that identifying
predictors of disease severity is a priority. We collect 58 clinical and biological variables, and …
predictors of disease severity is a priority. We collect 58 clinical and biological variables, and …
Study of thoracic CT in COVID-19: the STOIC project
MP Revel, S Boussouar, C de Margerie-Mellon, I Saab… - Radiology, 2021 - pubs.rsna.org
Background There are conflicting data regarding the diagnostic performance of chest CT for
COVID-19 pneumonia. Disease extent at CT has been reported to influence prognosis …
COVID-19 pneumonia. Disease extent at CT has been reported to influence prognosis …
Machine learning for medical imaging‐based COVID‐19 detection and diagnosis
R Rehouma, M Buchert… - International Journal of …, 2021 - Wiley Online Library
The novel coronavirus disease 2019 (COVID‐19) is considered to be a significant health
challenge worldwide because of its rapid human‐to‐human transmission, leading to a rise …
challenge worldwide because of its rapid human‐to‐human transmission, leading to a rise …
[HTML][HTML] Covid-19 detection via deep neural network and occlusion sensitivity maps
Deep learning approaches have attracted a lot of attention in the automatic detection of
Covid-19 and transfer learning is the most common approach. However, majority of the pre …
Covid-19 and transfer learning is the most common approach. However, majority of the pre …
Study of different deep learning methods for coronavirus (COVID-19) pandemic: Taxonomy, survey and insights
COVID-19 has evolved into one of the most severe and acute illnesses. The number of
deaths continues to climb despite the development of vaccines and new strains of the virus …
deaths continues to climb despite the development of vaccines and new strains of the virus …
[HTML][HTML] Radiology indispensable for tracking COVID-19
J Li, X Long, X Wang, F Fang, X Lv, D Zhang… - Diagnostic and …, 2021 - Elsevier
With the rapid spread of COVID-19 worldwide, early detection and efficient isolation of
suspected patients are especially important to prevent the transmission. Although nucleic …
suspected patients are especially important to prevent the transmission. Although nucleic …
Diagnostic performance of CO-RADS for COVID-19: a systematic review and meta-analysis
G Liu, Y Chen, A Runa, J Liu - European Radiology, 2022 - Springer
Objectives To investigate the diagnostic performance of the coronavirus disease 2019
(COVID-19) Reporting and Data System (CO-RADS) for detecting COVID-19. Methods We …
(COVID-19) Reporting and Data System (CO-RADS) for detecting COVID-19. Methods We …
[PDF][PDF] Association among CO-RADS score, co-morbid diseases, and short-term prognosis in COVID-19 infection.
OBJECTIVE: CO-RADS scoring system is used as a diagnostic tool. However, the data
about its association with co-morbid diseases and effectiveness in predicting intensive care …
about its association with co-morbid diseases and effectiveness in predicting intensive care …