{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"omics_type":["Unknown"],"volume":["8(15)"],"submitter":["Wang C"],"pubmed_abstract":["<h4>Background</h4>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.<h4>Methods</h4>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"],"journal":["Annals of translational medicine"],"pagination":["935"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC7475384"],"repository":["biostudies-literature"],"pubmed_title":["Temporal changes of COVID-19 pneumonia by mass evaluation using CT: a retrospective multi-center study."],"pmcid":["PMC7475384"],"pubmed_authors":["Liu J","Wang C","Su M","Shu J","Zhang M","Zhao T","Ren D","Zhao Z","Yao W","Huang P","Wang L","Liu Y","Shen Z","Lin B","Zheng H","Xia J","Yang Y","Wang Q","Ji W","Gao Y","Ma J","Liu B","Ruan G","Cheng J"],"additional_accession":[]},"is_claimable":false,"name":"Temporal changes of COVID-19 pneumonia by mass evaluation using CT: a retrospective multi-center study.","description":"<h4>Background</h4>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.<h4>Methods</h4>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","dates":{"release":"2020-01-01T00:00:00Z","publication":"2020 Aug","modification":"2025-04-25T17:42:32.242Z","creation":"2025-04-25T17:42:32.242Z"},"accession":"S-EPMC7475384","cross_references":{"pubmed":["32953735"],"doi":["10.21037/atm-20-4004"]}}