Application with deep learning models for COVID-19 diagnosis

Fuat Türk; Yunus Kökver

doi:10.35377/saucis...1085625

EN

Application with deep learning models for COVID-19 diagnosis

Abstract

COVID-19 is a deadly virus that first appeared in late 2019 and spread rapidly around the world. Understanding and classifying computed tomography images (CT) is extremely important for the diagnosis of COVID-19. Many case classification studies face many problems, especially unbalanced and insufficient data. For this reason, deep learning methods have a great importance for the diagnosis of COVID-19. Therefore, we had the opportunity to study the architectures of NasNet-Mobile, DenseNet and Nasnet-Mobile+DenseNet with the dataset we have merged. The dataset we have merged for COVID-19 is divided into 3 separate classes: Normal, COVID-19, and Pneumonia. We obtained the accuracy 87.16%, 93.38% and 93.72% for the NasNet-Mobile, DenseNet and NasNet-Mobile+DenseNet architectures for the classification, respectively. The results once again demonstrate the importance of Deep Learning methods for the diagnosis of COVID-19.

Keywords

References

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Details

Primary Language

English

Subjects

Artificial Intelligence

Journal Section

Research Article

Authors

Fuat Türk ^*
0000-0001-8159-360X
Türkiye

Yunus Kökver
0000-0002-9864-2866
Türkiye

Publication Date

August 31, 2022

Submission Date

March 10, 2022

Acceptance Date

June 19, 2022

Published in Issue

Year 2022 Volume: 5 Number: 2

DOI

https://doi.org/10.35377/saucis...1085625

IZ

https://izlik.org/JA25TL36UY

Cite

RIS / Bibtex

APA

Türk, F., & Kökver, Y. (2022). Application with deep learning models for COVID-19 diagnosis. Sakarya University Journal of Computer and Information Sciences, 5(2), 169-180. https://doi.org/10.35377/saucis...1085625

AMA

1.Türk F, Kökver Y. Application with deep learning models for COVID-19 diagnosis. SAUCIS. 2022;5(2):169-180. doi:10.35377/saucis.1085625

Chicago

Türk, Fuat, and Yunus Kökver. 2022. “Application With Deep Learning Models for COVID-19 Diagnosis”. Sakarya University Journal of Computer and Information Sciences 5 (2): 169-80. https://doi.org/10.35377/saucis. 1085625.

EndNote

Türk F, Kökver Y (August 1, 2022) Application with deep learning models for COVID-19 diagnosis. Sakarya University Journal of Computer and Information Sciences 5 2 169–180.

IEEE

[1]F. Türk and Y. Kökver, “Application with deep learning models for COVID-19 diagnosis”, SAUCIS, vol. 5, no. 2, pp. 169–180, Aug. 2022, doi: 10.35377/saucis...1085625.

ISNAD

Türk, Fuat - Kökver, Yunus. “Application With Deep Learning Models for COVID-19 Diagnosis”. Sakarya University Journal of Computer and Information Sciences 5/2 (August 1, 2022): 169-180. https://doi.org/10.35377/saucis. 1085625.

JAMA

1.Türk F, Kökver Y. Application with deep learning models for COVID-19 diagnosis. SAUCIS. 2022;5:169–180.

MLA

Türk, Fuat, and Yunus Kökver. “Application With Deep Learning Models for COVID-19 Diagnosis”. Sakarya University Journal of Computer and Information Sciences, vol. 5, no. 2, Aug. 2022, pp. 169-80, doi:10.35377/saucis. 1085625.

Vancouver

1.Fuat Türk, Yunus Kökver. Application with deep learning models for COVID-19 diagnosis. SAUCIS. 2022 Aug. 1;5(2):169-80. doi:10.35377/saucis. 1085625