COVID-19 pneumonia patient without clear epidemiological history outside Wuhan: An analysis of the radiographic and clinical features

Lin, Chen; Chen, Zixian; Xie, Bin; Sun, Zhujian; Ding, Yuxiao; Li, Xiaogang; Niu, Meng; Guo, Shunlin; Lei, Junqiang

doi:10.1016/j.clinimag.2020.04.023

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Cited by 4 publications

(1 citation statement)

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“…Several reports have described pulmonary involvement as the most common clinical presentation of severe infection with the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus (COVID-19) [1][2][3][4]. As the outbreak progressed to a global pandemic, extrapulmonary manifestations were increasingly identified, most often occurring concomitantly with pulmonary disease [5][6].…”

Section: Introductionmentioning

confidence: 99%

Acute Effusive Pericarditis: A Late Complication of COVID-19

Fox¹,

Prokup²,

Butson³

et al. 2020

Cureus

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Section: Introductionmentioning

confidence: 99%

Acute Effusive Pericarditis: A Late Complication of COVID-19

Fox¹,

Prokup²,

Butson³

et al. 2020

Cureus

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show abstract

The relationship between CT severity infections and oxygen saturation in patients infected with COVID-19, a cohort study

Qadir

Kakamad

Abdullah

et al. 2022

Annals of Medicine &Amp; Surgery

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CoV2-Detect-Net: Design of COVID-19 prediction model based on hybrid DE-PSO with SVM using chest X-ray images

Dixit

Mani

Bansal

2021

Information Sciences

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For Covid-19 suspected cases, it is critical to diagnose them accurately and rapidly so that they can be isolated and provided with required medical care. A self-learning automation model will be helpful to diagnose the COVID-19 suspected individual using chest X-rays. AI based designs, which utilizes chest X-rays, have been recently proposed for the detection of COVID-19. However, these approaches are either using non-public database or having a complex design. In this study we have proposed a novel framework for real time detection of coronavirus patients without manual intervention. In our framework, we have introduced a 3-step process in which initially K-means clustering, and feature extraction is performed as a data pre-processing step. In the second step, the selected features are optimized by a novel feature optimization approach based on hybrid differential evolution algorithm and particle swarm optimization. The optimized features are then feed forwarded to SVM classifier. Empirical results show that our proposed model is able to achieve 99.34% accuracy. This shows that our model is robust and sustainable in diagnosis of COVID-19 infected individual.

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COVID-19 pneumonia patient without clear epidemiological history outside Wuhan: An analysis of the radiographic and clinical features

Abstract: The purpose of this case report is to describe the radiographic and clinical features of a COVID-19 pneumonia patient without clear epidemiological history outside Wuhan, China.

Cited by 4 publications

References 5 publications

Acute Effusive Pericarditis: A Late Complication of COVID-19

Acute Effusive Pericarditis: A Late Complication of COVID-19

The relationship between CT severity infections and oxygen saturation in patients infected with COVID-19, a cohort study

CoV2-Detect-Net: Design of COVID-19 prediction model based on hybrid DE-PSO with SVM using chest X-ray images

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