COVID-19 Severity Classification Using aHierarchical Classification Deep Learning Modeldoi:10.1007/978-3-031-07704-3_36One of the most important situations in recent years has been originated by the 2019 Coronavirus disease (COVID-19). Nowadays this disease continues to cause a large number of ...
We employed deep-learning algorithms to predict COVID-19 lung disease severity, including RCNN, VGG, EfficientNet, and Transformer (VIT) models. Using a new dataset and multi-class classification, we found that ResNet101 is the best model, with 99.5% accuracy on SGD in multi-class prediction...
20. It is calculated from the summation of lesion scores in five lung lobes and is used to categorize the severity of lung involvement and help determine the proper therapeutic management and prognosis21,22. TSS reflects the clinical classification of COVID-1922. It has also been shown to ...
According to the severity classification, proportion of severe COVID-19 cases who showed severe clinical outcomes including ICU care, application of mechanical ventilation or ECMO, and death were higher in asthma group (9.1% vs. 4.6%, P < 0.001). In asthma patients, there was no ...
Social media platforms, such as Twitter, allow users to share their thoughts and opinions on various topics, including pandemics like COVID-19. This data can be used to analyze public sentiment and assess the severity of different Corona variants. In this study, a new framework called SENSECOR...
We found a significantly increased SARS-CoV-2-specific antibody response in severe COVID-19 patients when compared to patients who experienced mild and moderate disease symptoms. This severity-associated antibody increase was dominated by IgG, with a disproportionate IgG subclass response dominated by ...
This type of model applies to certain, non-fatal diseases without severity but is also useful as a first approximation of the behavior models. In these models, individuals are more likely to undertake a given action as more of their neighbors do the same, but they can also randomly stop ...
Automatic classification of severity of COVID-19 patients using texture feature and random forest based on computed tomography images Finally, using the extracted features, CT images of each person are classified using random forest (RF) as an ensemble method based on majority voting ... N Amini...
[56] invested ATR-FTIR for COVID-19 severity classification. The study indicated that ATR-FTIR was a promising method for COVID-19 monitoring in real time. Clinical laboratory professionals may readily carry out the sample preparation and spectrum collection procedures established here due to their...
Segmentation of lung lobes and lesions in chest CT for the classification of COVID-19 severity ArticleOpen access28 November 2023 COVID-19 infection segmentation using hybrid deep learning and image processing techniques ArticleOpen access20 December 2023 ...