Identifying features and severity of 2019 coronavirus disease (COVID-19) on admission based on thoracic computer tomography

Mo, Z.; Zhang, Q.; Luo, X. W.; Zhang, Y.; Qin, T.; Zhu, Y. Z.

Mo, Z.; Zhang, Q.; Luo, X. W.; Zhang, Y.; Qin, T.; Zhu, Y. Z..

International Journal of Radiation Research ; 20(3):579-585, 2022.

Article in English | ProQuest Central | ID: covidwho-2026842

Keywords

Medical Sciences--Radiology And Nuclear Medicine; Laboratories; Pleural effusion; Tomography; Signs; Pneumonia; Regression analysis; Severe acute respiratory syndrome coronavirus 2; Liver; Computed tomography; Cytokines; Epidemics; Viral diseases; Logistics; Respiratory diseases; Coronaviruses; Statistical analysis; Disease transmission; Proteins; COVID-19; China

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Full text: Available Collection: Databases of international organizations Database: ProQuest Central Type of study: Prognostic study Language: English Journal: International Journal of Radiation Research Year: 2022 Document Type: Article

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