Author: Zhiqi Yang; Daiying Lin; Xiaofeng Chen; Jinming Qiu; Shengkai Li; Ruibin Huang; Hongfu Sun; Yuting Liao; Jianning Xiao; Yanyan Tang; Guorui Liu; Renhua Wu; Xiangguang Chen; Zhuozhi Dai
Title: Distinguishing COVID-19 from influenza pneumonia in the early stage through CT imaging and clinical features Document date: 2020_4_22
ID: ggwh91cc_6
Snippet: is the (which was not peer-reviewed) The copyright holder for this preprint . https://doi.org/10.1101/2020.04. 17.20061242 doi: medRxiv preprint on chest CT results and found the average sensitivity of 80% and specificity of 84% (12) . However, we realized that about 44% of the viral pneumonia cases were Human Rhinovirus, and influenza pneumonia only accounted for about 15%. To our knowledge, no study has explored the differences between COVID-19.....
Document: is the (which was not peer-reviewed) The copyright holder for this preprint . https://doi.org/10.1101/2020.04. 17.20061242 doi: medRxiv preprint on chest CT results and found the average sensitivity of 80% and specificity of 84% (12) . However, we realized that about 44% of the viral pneumonia cases were Human Rhinovirus, and influenza pneumonia only accounted for about 15%. To our knowledge, no study has explored the differences between COVID-19 and influenza using CT imaging and clinical features. In this study, we aim to identify differences in CT imaging and clinical features between COVID-19 and influenza pneumonia in the early stage, and to identify the most valuable features in distinguishing COVID-19 from influenza pneumonia, based on multi-center data.
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