Research Article

Prediction of Covid-19 disease with Resnet-101 deep learning architecture using Computerized Tomography images

Volume: 11 Number: 2 June 29, 2022
TR EN

Prediction of Covid-19 disease with Resnet-101 deep learning architecture using Computerized Tomography images

Abstract

Many pandemics have caused the deaths of millions of people in world history from past to present. Therefore, the measures to be taken in the prevention of pandemics are of great importance. In addition to the precautions, it is very important to be able to diagnose the disease early. The most recent pandemic occurred in the world is the COVID-19 outbreak that emerged in China in late 2019. In this study, Computerized Tomography images of 746 patients taken from an open source (GitHub) website were used. Images were analyzed using the Resnet-101 model, which is one of the deep learning architectures. Classification process was carried out with the created Resnet-101 model. With the Resnet-101 model, individuals with Covid-19 disease were tried to be identified. The Resnet-101 model detected individuals with Covid-19 disease with an accuracy rate of 94.29%.

Keywords

Thanks

We would like to thank Zhao et al. who opened the data set used in the study for open access.

References

  1. Çalışkan, A. (2019). XIX. Yüzyıl ve XX. Yüzyıl başlarında Maraş ve kazalarında salgın hastalıklar ve salgın hastalıklara karşı alınan önlemler. Paradigma Akademi.
  2. Benedictow, O. J., & Benedictow, O. L. (2004). The Black Death, 1346-1353: the complete history. Boydell & Brewer.
  3. Condrau, F. (2020). Samuel K. Cohn Jr., Epidemics: Hate and Compassion from the Plague of Athens to AIDS. Social History of Medicine.
  4. Bung, N., Krishnan, S. R., Bulusu, G., & Roy, A. (2020). De novo design of new chemical entities (NCEs) for SARS-CoV-2 using artificial intelligence.
  5. Dikmen, A. U., KINA, M. H., Özkan, S., & İlhan, M. N. (2020). Epidemiology of COVID-19: What We Learn From Pandemic. Journal of Biotechnology and Strategic Health Research, 4, 29-36.
  6. Macleod, I., & Heath, N. (2008). Cone-beam computed tomography (CBCT) in dental practice. Dental update, 35(9), 590-598.
  7. Li, X., Zeng, X., Liu, B., & Yu, Y. (2020a). COVID-19 infection presenting with CT halo sign. Radiology: Cardiothoracic Imaging, 2(1), e200026. doi: 10.1148/ryct.2020200026.
  8. Fang, Y., Zhang, H., Xu, Y., Xie, J., Pang, P., & Ji, W. (2020). CT manifestations of two cases of 2019 novel coronavirus (2019-nCoV) pneumonia. Radiology, 295(1), 208-209.

Details

Primary Language

English

Subjects

Engineering

Journal Section

Research Article

Publication Date

June 29, 2022

Submission Date

March 30, 2022

Acceptance Date

April 26, 2022

Published in Issue

Year 2022 Volume: 11 Number: 2

APA
Aksoy, B., & Salman, O. K. M. (2022). Prediction of Covid-19 disease with Resnet-101 deep learning architecture using Computerized Tomography images. Turkish Journal of Nature and Science, 11(2), 36-42. https://doi.org/10.46810/tdfd.1095624
AMA
1.Aksoy B, Salman OKM. Prediction of Covid-19 disease with Resnet-101 deep learning architecture using Computerized Tomography images. TJNS. 2022;11(2):36-42. doi:10.46810/tdfd.1095624
Chicago
Aksoy, Bekir, and Osamah Khaled Musleh Salman. 2022. “Prediction of Covid-19 Disease With Resnet-101 Deep Learning Architecture Using Computerized Tomography Images”. Turkish Journal of Nature and Science 11 (2): 36-42. https://doi.org/10.46810/tdfd.1095624.
EndNote
Aksoy B, Salman OKM (June 1, 2022) Prediction of Covid-19 disease with Resnet-101 deep learning architecture using Computerized Tomography images. Turkish Journal of Nature and Science 11 2 36–42.
IEEE
[1]B. Aksoy and O. K. M. Salman, “Prediction of Covid-19 disease with Resnet-101 deep learning architecture using Computerized Tomography images”, TJNS, vol. 11, no. 2, pp. 36–42, June 2022, doi: 10.46810/tdfd.1095624.
ISNAD
Aksoy, Bekir - Salman, Osamah Khaled Musleh. “Prediction of Covid-19 Disease With Resnet-101 Deep Learning Architecture Using Computerized Tomography Images”. Turkish Journal of Nature and Science 11/2 (June 1, 2022): 36-42. https://doi.org/10.46810/tdfd.1095624.
JAMA
1.Aksoy B, Salman OKM. Prediction of Covid-19 disease with Resnet-101 deep learning architecture using Computerized Tomography images. TJNS. 2022;11:36–42.
MLA
Aksoy, Bekir, and Osamah Khaled Musleh Salman. “Prediction of Covid-19 Disease With Resnet-101 Deep Learning Architecture Using Computerized Tomography Images”. Turkish Journal of Nature and Science, vol. 11, no. 2, June 2022, pp. 36-42, doi:10.46810/tdfd.1095624.
Vancouver
1.Bekir Aksoy, Osamah Khaled Musleh Salman. Prediction of Covid-19 disease with Resnet-101 deep learning architecture using Computerized Tomography images. TJNS. 2022 Jun. 1;11(2):36-42. doi:10.46810/tdfd.1095624

Cited By