Development of a quantitative segmentation model to assess the effect of comorbidity on patients with COVID-19

Development of a quantitative segmentation model to assess the effect of comorbidity on patients with COVID-19

Abstract Background The coronavirus disease 2019 (COVID-19) has brought a global disaster. Quantitative lesions may provide the radiological evidence of the severity of pneumonia and further to assess the effect of comorbidity on patients with COVID-19. Methods 294 patients with COVID-19 were enroll...

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Bibliographic Details
Main Authors: Cui Zhang, Guangzhao Yang, Chunxian Cai, Zhihua Xu, Hai Wu, Youmin Guo, Zongyu Xie, Hengfeng Shi, Guohua Cheng, Jian Wang
Format: Article
Language:English
Published: BMC 2020-10-01
Series:European Journal of Medical Research
Subjects:
Comorbidity
COVID-19
Deep learning
X-ray computed tomography
Online Access:http://link.springer.com/article/10.1186/s40001-020-00450-1

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http://link.springer.com/article/10.1186/s40001-020-00450-1

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