An intelligent detection system for covid-19 diagnosis using ct-images
Other Title(s)
نظام كشف ذكي لتشخيص كوفيد-19 باستخدام الصور المقطعية
Joint Authors
Ahmad, Aya Husam al-Din Mahmud
Abd al-Qadir, Halah Mansur
Hasan, Amirah M.
Source
Journal of Engineering Sciences
Issue
Vol. 49, Issue 4 (31 Jul. 2021), pp.476-508, 33 p.
Publisher
Assiut University Faculty of Engineering
Publication Date
2021-07-31
Country of Publication
Egypt
No. of Pages
33
Main Subjects
Topics
- Artificial intelligence
- Machine learning
- Algorithms
- Computed tomography
- Neural networks(Computer science)
Abstract EN
Early classification of the Coronavirus disease (COVID-19) is necessary to control its rapid spread and save patients' lives.
The fast spread of COVID-19 has increased the diagnostic encumbrance of radiologists.
Therefore, clinicians need to quickly assess if a patient has COVID-19 or not.
Artificial Intelligence (AI) has shown promising results in healthcare.
So, this paper proposed a computer-aided intelligence model that can identify positive COVID-19 cases.
It presented the pipeline of medicinal imaging and examination methods involved in COVID-19 image acquirement, segmentation, and diagnosis, using Computed Tomography (CT) images.
This paper introduced two effective models for single machine learning (SML) and ensemble machine learning (EML) with 10-fold cross validation, to detect cases of COVID-19.
The first classification model (SML) was applied with different algorithms, such as Decision Tree (DT), Artificial Neural Networks (ANN), and Support Vector Machines (SVM).
Results showed that the performance of the SVM surpassed other classifiers with a 98.85 % accuracy.
The second classification model (EML) was applied with several algorithms, such as Random Forest (RF), Voting, and Bagging, to increase its accuracy up to 99.60% , especially using the Bagging classifier.
Finally, the results of the two proposed models showed better performance compared with other recent studies.
However, the EML showed an even better performance than SML and is recommended for use in real-time.
American Psychological Association (APA)
Hasan, Amirah M.& Ahmad, Aya Husam al-Din Mahmud& Abd al-Qadir, Halah Mansur. 2021. An intelligent detection system for covid-19 diagnosis using ct-images. Journal of Engineering Sciences،Vol. 49, no. 4, pp.476-508.
https://search.emarefa.net/detail/BIM-1240614
Modern Language Association (MLA)
Hasan, Amirah M.…[et al.]. An intelligent detection system for covid-19 diagnosis using ct-images. Journal of Engineering Sciences Vol. 49, no. 4 (Jul. 2021), pp.476-508.
https://search.emarefa.net/detail/BIM-1240614
American Medical Association (AMA)
Hasan, Amirah M.& Ahmad, Aya Husam al-Din Mahmud& Abd al-Qadir, Halah Mansur. An intelligent detection system for covid-19 diagnosis using ct-images. Journal of Engineering Sciences. 2021. Vol. 49, no. 4, pp.476-508.
https://search.emarefa.net/detail/BIM-1240614
Data Type
Journal Articles
Language
English
Notes
-
Record ID
BIM-1240614