A Comparative Study on COVID-19 Prediction Using Deep Learning and Machine Learning Algorithms: A Case Study on Performance Analysis

Hilal Arslan; Orhan Er

doi:10.35377/saucis...932400

EN

A Comparative Study on COVID-19 Prediction Using Deep Learning and Machine Learning Algorithms: A Case Study on Performance Analysis

Abstract

COVID-19 disease has been the most important disease recently and has affected serious number of people in the world. There is not proven treatment method yet and early diagnosis of COVID-19 is crucial to prevent spread of the disease. Laboratory data can be easily accessed in about 15 minutes, and cheaper than the cost of other COVID-19 detection methods such as CT imaging and RT-PCR test. In this study, we perform a comparative study for COVID-19 prediction using machine learning and deep learning algorithms from laboratory findings. For this purpose, nine different machine learning algorithms including different structures as well as deep neural network classifier are evaluated and compared. Experimental results conduct that cosine k-nearest neighbor classifier achieves better accuracy with 89% among other machine learning algorithms. Furthermore, deep neural network classifier achieves an accuracy of 90.3% when one hidden layer including 60 neurons is used to detect COVID-19 disease from laboratory findings data.

Keywords

References

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Details

Primary Language

English

Subjects

Software Engineering (Other)

Journal Section

Research Article

Authors

Hilal Arslan ^*
0000-0002-6449-6952
Türkiye

Orhan Er
0000-0002-4732-9490
Türkiye

Publication Date

April 30, 2022

Submission Date

May 4, 2021

Acceptance Date

March 29, 2022

Published in Issue

Year 2022 Volume: 5 Number: 1

DOI

https://doi.org/10.35377/saucis...932400

IZ

https://izlik.org/JA48ZF87PM

Cite

RIS / Bibtex

APA

Arslan, H., & Er, O. (2022). A Comparative Study on COVID-19 Prediction Using Deep Learning and Machine Learning Algorithms: A Case Study on Performance Analysis. Sakarya University Journal of Computer and Information Sciences, 5(1), 71-83. https://doi.org/10.35377/saucis...932400

AMA

1.Arslan H, Er O. A Comparative Study on COVID-19 Prediction Using Deep Learning and Machine Learning Algorithms: A Case Study on Performance Analysis. SAUCIS. 2022;5(1):71-83. doi:10.35377/saucis.932400

Chicago

Arslan, Hilal, and Orhan Er. 2022. “A Comparative Study on COVID-19 Prediction Using Deep Learning and Machine Learning Algorithms: A Case Study on Performance Analysis”. Sakarya University Journal of Computer and Information Sciences 5 (1): 71-83. https://doi.org/10.35377/saucis. 932400.

EndNote

Arslan H, Er O (April 1, 2022) A Comparative Study on COVID-19 Prediction Using Deep Learning and Machine Learning Algorithms: A Case Study on Performance Analysis. Sakarya University Journal of Computer and Information Sciences 5 1 71–83.

IEEE

[1]H. Arslan and O. Er, “A Comparative Study on COVID-19 Prediction Using Deep Learning and Machine Learning Algorithms: A Case Study on Performance Analysis”, SAUCIS, vol. 5, no. 1, pp. 71–83, Apr. 2022, doi: 10.35377/saucis...932400.

ISNAD

Arslan, Hilal - Er, Orhan. “A Comparative Study on COVID-19 Prediction Using Deep Learning and Machine Learning Algorithms: A Case Study on Performance Analysis”. Sakarya University Journal of Computer and Information Sciences 5/1 (April 1, 2022): 71-83. https://doi.org/10.35377/saucis. 932400.

JAMA

1.Arslan H, Er O. A Comparative Study on COVID-19 Prediction Using Deep Learning and Machine Learning Algorithms: A Case Study on Performance Analysis. SAUCIS. 2022;5:71–83.

MLA

Arslan, Hilal, and Orhan Er. “A Comparative Study on COVID-19 Prediction Using Deep Learning and Machine Learning Algorithms: A Case Study on Performance Analysis”. Sakarya University Journal of Computer and Information Sciences, vol. 5, no. 1, Apr. 2022, pp. 71-83, doi:10.35377/saucis. 932400.

Vancouver

1.Hilal Arslan, Orhan Er. A Comparative Study on COVID-19 Prediction Using Deep Learning and Machine Learning Algorithms: A Case Study on Performance Analysis. SAUCIS. 2022 Apr. 1;5(1):71-83. doi:10.35377/saucis. 932400