Using Artificial Intelligence to Detect COVID-19 and Community-acquired Pneumonia Based on Pulmonary CT: Evaluation of the Diagnostic Accuracy

@article{Li2020UsingAI,
  title={Using Artificial Intelligence to Detect COVID-19 and Community-acquired Pneumonia Based on Pulmonary CT: Evaluation of the Diagnostic Accuracy},
  author={Lin Li and Lixin Qin and Zeguo Xu and Youbing Yin and Xin Wang and Bin Kong and Junjie Bai and Yi Lu and Zhenghan Fang and Qi Song and Kunlin Cao and Daliang Liu and Guisheng Wang and Qizhong Xu and Xisheng Fang and Shiqin Zhang and Juan Xia and Jun Xia},
  journal={Radiology},
  year={2020},
  volume={296},
  pages={200905}
}
  • Lin Li, Lixin Qin, +15 authors Jun Xia
  • Published 2020
  • Medicine
  • Radiology
Background Coronavirus disease 2019 (COVID-19) has widely spread all over the world since the beginning of 2020. It is desirable to develop automatic and accurate detection of COVID-19 using chest CT. Purpose To develop a fully automatic framework to detect COVID-19 using chest CT and evaluate its performance. Materials and Methods In this retrospective and multicenter study, a deep learning model, the COVID-19 detection neural network (COVNet), was developed to extract visual features from… Expand
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