| Autor: |
Xiao-Ping Liu, Xu Yang, Miao Xiong, Xuanyu Mao, Xiaoqing Jin, Zhiqiang Li, Shuang Zhou, Hang Chang |
| Jazyk: |
angličtina |
| Rok vydání: |
2022 |
| Předmět: |
|
| Zdroj: |
Frontiers in Public Health, Vol 10 (2022) |
| Druh dokumentu: |
article |
| ISSN: |
2296-2565 |
| DOI: |
10.3389/fpubh.2022.1004117 |
| Popis: |
Coronavirus Disease 2019 (COVID-19) is currently a global pandemic, and early screening 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 from two independent hospitals with 419 patients. We identified the vasculature-like signals from CT images and found that, compared to healthy and community acquired pneumonia (CAP) patients, COVID-19 patients display a significantly higher abundance of these signals. Furthermore, unsupervised feature learning led to the discovery of clinical-relevant imaging biomarkers from the vasculature-like signals for accurate and sensitive COVID-19 screening that have been double-blindly validated in an independent hospital (sensitivity: 0.941, specificity: 0.920, AUC: 0.971, accuracy 0.931, F1 score: 0.929). Our findings could open a new avenue to assist screening of COVID-19 patients. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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