Institution
Chinese PLA General Hospital
Healthcare•Beijing, China•
About: Chinese PLA General Hospital is a healthcare organization based out in Beijing, China. It is known for research contribution in the topics: Population & Cancer. The organization has 18037 authors who have published 12349 publications receiving 184803 citations. The organization is also known as: 301 Military Hospital.
Topics: Population, Cancer, Transplantation, Mesenchymal stem cell, Cell growth
Papers published on a yearly basis
Papers
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TL;DR: O surto do novo coronavÃrus (COVID-19) em Wuhan, China, iniciado em dezembro de 2019, evoluiu para se tornar uma pandemia global A.
6,850 citations
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NewYork–Presbyterian Hospital1, University of Insubria2, University of Texas Health Science Center at Houston3, Chinese PLA General Hospital4, University of Vermont Medical Center5, Harvard University6, Beth Israel Deaconess Medical Center7, Loyola University Medical Center8, University of Chicago9, University of Milan10, Auckland City Hospital11, St Thomas' Hospital12, Hofstra University13, University of Michigan14, Hamilton Health Sciences15, Population Health Research Institute16, Ottawa Hospital Research Institute17, Brigham and Women's Hospital18, Vanderbilt University19, Universidad Católica San Antonio de Murcia20, University of Mainz21, McMaster University22, Aalborg University23, University of Liverpool24
TL;DR: The current understanding of the pathogenesis, epidemiology, management and outcomes of patients with COVID-19 who develop venous or arterial thrombosis, and of those with preexistingThrombotic disease who develop CO VID-19 are reviewed.
2,222 citations
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TL;DR: A deep learning model was developed to extract visual features from volumetric chest CT scans for the detection of coronavirus 2019 and differentiate it from community-acquired pneumonia and other lung conditions.
Abstract: 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 volumetric chest CT scans for the detection of COVID-19. CT scans of community-acquired pneumonia (CAP) and other non-pneumonia abnormalities were included to test the robustness of the model. The datasets were collected from six hospitals between August 2016 and February 2020. Diagnostic performance was assessed with the area under the receiver operating characteristic curve, sensitivity, and specificity. Results The collected dataset consisted of 4352 chest CT scans from 3322 patients. The average patient age (±standard deviation) was 49 years ± 15, and there were slightly more men than women (1838 vs 1484, respectively; P = .29). The per-scan sensitivity and specificity for detecting COVID-19 in the independent test set was 90% (95% confidence interval [CI]: 83%, 94%; 114 of 127 scans) and 96% (95% CI: 93%, 98%; 294 of 307 scans), respectively, with an area under the receiver operating characteristic curve of 0.96 (P < .001). The per-scan sensitivity and specificity for detecting CAP in the independent test set was 87% (152 of 175 scans) and 92% (239 of 259 scans), respectively, with an area under the receiver operating characteristic curve of 0.95 (95% CI: 0.93, 0.97). Conclusion A deep learning model can accurately detect coronavirus 2019 and differentiate it from community-acquired pneumonia and other lung conditions. © RSNA, 2020 Online supplemental material is available for this article.
1,505 citations
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1,447 citations
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TL;DR: It is found that digestive symptoms are common in patients with COVID-19 and that the index of suspicion may need to be raised earlier in at-risk patients presenting with digestive symptoms, but further large sample studies are needed to confirm these findings.
1,397 citations
Authors
Showing all 18235 results
Name | H-index | Papers | Citations |
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Jun Zhao | 1 | 2 | 12 |
Huan Wu | 1 | 1 | 7 |
Rongjian Lu | 1 | 1 | 7 |
Qing Ang | 1 | 1 | 7 |
Xinxin Wang | 1 | 1 | 1 |
Lu Liu | 1 | 1 | 2 |
Y.H. Liu | 1 | 1 | 2 |
Ai Ting Chen | 1 | 1 | 16 |
Fu-Lian Han | 1 | 1 | 1 |
Ya Gu | 1 | 3 | 5 |
Yuting Zou | 1 | 2 | 5 |
Yuanbo Shi | 1 | 1 | 1 |
Zhiqi Mao | 1 | 1 | 22 |
Y Yang | 1 | 1 | 1 |
Yundai Chen | 1 | 1 | 19 |