Selected article for: "clinical feature and coronavirus disease"
Author: Mao, X.; Liu, X.-P.; Yang, X.; Mao, J.-H.; Xiong, M.; Zhou, S.; Chang, H.
Title: Development and validation of chest CT-based imaging biomarkers for early stage COVID-19 screening
  • Cord-id: nhxrpy37
  • Document date: 2020_5_20
    • ID: nhxrpy37
    Snippet: Coronavirus Disease 2019 (COVID-19) is currently a global pandemic, and the early screening of COVID-19 is one of the key factors for COVID-19 control and treatment. Here, we developed and validated chest CT-based imaging biomarkers for COVID-19 patient screening. We identified the vasculature-like signals from CT images and found that, compared to healthy and community acquired pneumonia (CAP) patients, the COVID-19 patients revealed significantly higher abundance of these signals. Furthermore,
    Document: Coronavirus Disease 2019 (COVID-19) is currently a global pandemic, and the early screening of COVID-19 is one of the key factors for COVID-19 control and treatment. Here, we developed and validated chest CT-based imaging biomarkers for COVID-19 patient screening. We identified the vasculature-like signals from CT images and found that, compared to healthy and community acquired pneumonia (CAP) patients, the COVID-19 patients revealed significantly higher abundance of these signals. Furthermore, unsupervised feature learning leads to the discovery of clinical-relevant imaging biomarkers from the vasculature-like signals for accurate and sensitive COVID-19 screening that has been double-blindly validated in an independent hospital (sensitivity: 0.941, specificity: 0.904, AUC: 0.952). Our findings could open a new avenue to assist screening of COVID-19 patients.

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