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ABSTRACT: Background
Coronavirus disease 2019 (COVID-19) has widely spread worldwide and caused a pandemic. Chest CT has been found to play an important role in the diagnosis and management of COVID-19. However, quantitatively assessing temporal changes of COVID-19 pneumonia over time using CT has still not been fully elucidated. The purpose of this study was to perform a longitudinal study to quantitatively assess temporal changes of COVID-19 pneumonia.Methods
This retrospective and multi-center study included patients with laboratory-confirmed COVID-19 infection from 16 hospitals between January 19 and March 27, 2020. Mass was used as an approach to quantitatively measure dynamic changes of pulmonary involvement in patients with COVID-19. Artificial intelligence (AI) was employed a
SUBMITTER: Wang C
PROVIDER: S-EPMC7475384 | biostudies-literature | 2020 Aug
REPOSITORIES: biostudies-literature