• Corpus ID: 214667444

Severity Assessment of Coronavirus Disease 2019 (COVID-19) Using Quantitative Features from Chest CT Images

@article{Tang2020SeverityAO,
  title={Severity Assessment of Coronavirus Disease 2019 (COVID-19) Using Quantitative Features from Chest CT Images},
  author={Zhenyu Tang and Wei Zhao and Xingzhi Xie and Zheng Zhong and Feng Shi and Jun Liu and Dinggang Shen},
  journal={ArXiv},
  year={2020},
  volume={abs/2003.11988}
}
Background: Chest computed tomography (CT) is recognized as an important tool for COVID-19 severity assessment. As the number of affected patients increase rapidly, manual severity assessment becomes a labor-intensive task, and may lead to delayed treatment. Purpose: Using machine learning method to realize automatic severity assessment (non-severe or severe) of COVID-19 based on chest CT images, and to explore the severity-related features from the resulting assessment model. Materials andโ€ฆย 

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