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. 2022 Jul 27:2022:9771212.
doi: 10.1155/2022/9771212. eCollection 2022.

An Empirical Analysis of an Optimized Pretrained Deep Learning Model for COVID-19 Diagnosis

S K B Sangeetha  1 , M Sandeep Kumar  2 , Deeba K  3 , Hariharan Rajadurai  4 , V Maheshwari  2 , Gemmachis Teshite Dalu  5
Affiliations

An Empirical Analysis of an Optimized Pretrained Deep Learning Model for COVID-19 Diagnosis

S K B Sangeetha et al. Comput Math Methods Med. .

Abstract

As a result of the COVID-19 outbreak, which has put the world in an unprecedented predicament, thousands of people have died. Data from structured and unstructured sources are combined to create user-friendly platforms for clinicians and researchers in an integrated bioinformatics approach. The diagnosis and treatment of COVID-19 disease can be accelerated using AI-based platforms. In the battle against the virus, however, researchers and decision-makers must contend with an ever-increasing volume of data, referred to as "big data." VGG19 and ResNet152V2 pretrained deep learning architectures were used in this study. With these datasets, we could train and fine-tune our model on lung ultrasound frames from healthy people as well as from patients with COVID-19 and pneumonia. In two separate experiments, we evaluated two different classes of predictive models: one against pneumonia and the other against non-COVID-19. COVID-19 can be detected and diagnosed accurately and efficiently using these models, according to the findings. Therefore, the use of these inexpensive and affordable deep learning methods should be considered as a reliable method for the diagnosis of COVID-19.

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Conflict of interest statement

The authors declare that there is no conflict of interest regarding the publication of this article.

Figures

Figure 1
Figure 1
Proposed VGG19-ResNet CNN architecture.
Figure 2
Figure 2
Normal images.
Figure 3
Figure 3
Pneumonia images.
Figure 4
Figure 4
COVID-19 images.
Figure 5
Figure 5
F-score comparison analysis.
Figure 6
Figure 6
Accuracy comparison analysis.
Figure 7
Figure 7
ROC curve: combined VGG19 and ResNet152V2.
Figure 8
Figure 8
Epoch comparison.
See this image and copyright information in PMC

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