CT Imaging Changes of Corona Virus Disease 2019 (COVID-19):A multi-center study in Southwest China

Li, Xiaoming; Zeng, Wenbing; Li, Xiang; Chen, Haonan; Shi, Linping; Li, Xinghui; Xiang, Hongnian; Cao, Yang; Chen, Hui; Liu, Chen; Wang, Jian

doi:10.21203/rs.3.rs-16974/v2

Cited by 2 publications

(1 citation statement)

References 10 publications

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“…Chest CT plays an vital role in differential diagnosis of COVID-19. Li X, etal reported that around 83% COVID-19 patients had more than two lobes involved, and most images were multiple lesions localized in the peripheral of bilateral lungs 18 . In this study, all patients received chest CT scans, the radiological features of lungs showed that 72.9% COVID-19 patients and 87.5% severe patients had bilateral pneumonia.…”

Section: Disscussionmentioning

confidence: 99%

Eosinopenia Phenotype in Patients with Coronavirus Disease 2019: A Multi-center Retrospective Study from Anhui, China

Cheng

Zhou

Zhu

et al. 2020

Preprint

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Background: Coronavirus disease 19 has become a global unprecedented pandemic infecting more than one millon people, which is declared by WHO as a international public health emergency. Eosinopenia may predict a poor prognosis of COVID-19. However, to date, there is no detailed analysis of the clinical characteristics of COVID-19 patients with eosinopenia. . We described clincial characteristics of patients with COIVD-19 and eosinopenia phenotype. Results:The median age of patients with COVID-19 was 39 years old, and 32 (54,2%) were male. Patients with severe type had higher proportions of dyspnea (50%) and gastrointestinal symptoms (50%) compared with mild or moderate patients.Laboratory findings indicated that lower counts of lymphocyte and eosnophils were observed in patients with severe type. Cough, sputum, and fatigue were more common symptoms in eosinopenia patients compared with non-eosinopenia patients.High proportion of comorbidities was observed in eosinopenia patients. Laboratory findings indicated that lymphocyte counts (median: 101 cells/μl ) in eosinopenia patients were significantly less than those of non-eosinopenia patients (median: 167 cells/μl, p<0.001). The use of corticosteroids therapy in COVID-19 patients with : medRxiv preprint eosinopenia were notably higher than those in patients with non-eosinopenia (50% vs 13.8%, respectively, p=0.005). Compared with parameters in non-eosinopenia patients, eosinopenia patients were more inclined to have less lymphocyte counts (OR value 6.566, 95%CI[1.101-39.173], p=0.039). InterpretationEosinopenia are very common in COVID-19 patient, particularly in severe patients.Common symptoms included fever, cough, sputum, and fatigue are frequent in eosinopenia patients. Eosinopenia may represent a novel phenotype in COVID-19, which needs further investigation.

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Section: Disscussionmentioning

confidence: 99%

Eosinopenia Phenotype in Patients with Coronavirus Disease 2019: A Multi-center Retrospective Study from Anhui, China

Cheng

Zhou

Zhu

et al. 2020

Preprint

View full text Add to dashboard Cite

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A Comprehensive Survey on the Data-Driven Approaches used for Tackling the COVID-19 Pandemic

Salameh,

Surakhi,

Khanafseh

2024

Wseas Transactions on Biology and Biomedicine

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The current evolution of Artificial Intelligence (AI) is fueled by the massive data sources generated by the Internet of Things (IoT), social media, and a diverse range of mobile and web applications. Machine learning (ML) and deep learning become the key to analyzing these data intelligently and developing complementary intelligent data-driven services in the healthcare sector. The world witnessed many AI-enabled tools that contributed to fighting against the COVID-19 pandemic and accelerated with unprecedented accuracy the development and the deployment of many countermeasures. The main objective of this study is to provide a comprehensive survey on the role of AI and ML methods in the healthcare sector. The study offers cases on how AI/ML can arm the world against future pandemics. Specifically, the study presents all available datasets, the main research problems related to COVID-19, and the solutions that AI and ML technologies offer. Finally, based on the analysis of the current literature, the limitations and open research challenges are highlighted. Our findings show that AI and ML technologies can play an essential role in COVID-19 forecasting, prediction, diagnosis, and analysis. In comparison, most of the previous works did not deploy a comprehensive framework that integrates the ML and DL with network security. This work emphasizes the mandate of including network security in all COVID-19 applications and providing complete and secure healthcare services.

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CT Imaging Changes of Corona Virus Disease 2019 (COVID-19):A multi-center study in Southwest China

Cited by 2 publications

References 10 publications

Eosinopenia Phenotype in Patients with Coronavirus Disease 2019: A Multi-center Retrospective Study from Anhui, China

Eosinopenia Phenotype in Patients with Coronavirus Disease 2019: A Multi-center Retrospective Study from Anhui, China

A Comprehensive Survey on the Data-Driven Approaches used for Tackling the COVID-19 Pandemic

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