A convolutional neural network for detecting COVID-19 from Chest X-ray Images
Joint Authors
Ahmad, Hana Muhsin
Abd Allah, Basmah Wail
Source
Iraqi Journal of Computer, Communications and Control Engineering
Issue
Vol. 22, Issue 3 (30 Sep. 2022), pp.1-14, 14 p.
Publisher
Publication Date
2022-09-30
Country of Publication
Iraq
No. of Pages
14
Main Subjects
Information Technology and Computer Science
Abstract EN
Since the global pandemic of COVID-19 has spread out, the use of Artificial Intelligence to analyze Chest X-Ray (CXR) image for COVID-19 diagnosis and patient treatment is becoming more important.
This research hypothesized that using COVID19 radiographic changes in the X-Ray images.
Artificial Intelligence (AI) systems may extract certain graphical elements regarding COVID-19 and offer a clinical diagnosis ahead of pathogenic test; therefore, saving vital time for disease prevention.
Employing 2614 CXR radiographs from Kaggle data collection of verified COVID-19 cases and healthy persons, a new Convolutional Neural Network (CNN) model that is inspired by the Xception architecture was presented for the diagnosis of coronavirus pneumonia infected patients.
The suggested technique reached an average validation accuracy of 0.99, precision of 0.95, recall of 0.92, and F1-score of 0.
95.
Finally, such findings revealed that the Deep Learning (DL) technique has the potential to decrease frontline radiologists' stress, enhance early diagnosis, treatment, and isolation; therefore, aid in epidemic control.
American Psychological Association (APA)
Abd Allah, Basmah Wail& Ahmad, Hana Muhsin. 2022. A convolutional neural network for detecting COVID-19 from Chest X-ray Images. Iraqi Journal of Computer, Communications and Control Engineering،Vol. 22, no. 3, pp.1-14.
https://search.emarefa.net/detail/BIM-1492769
Modern Language Association (MLA)
Abd Allah, Basmah Wail& Ahmad, Hana Muhsin. A convolutional neural network for detecting COVID-19 from Chest X-ray Images. Iraqi Journal of Computer, Communications and Control Engineering Vol. 22, no. 3 (Sep. 2022), pp.1-14.
https://search.emarefa.net/detail/BIM-1492769
American Medical Association (AMA)
Abd Allah, Basmah Wail& Ahmad, Hana Muhsin. A convolutional neural network for detecting COVID-19 from Chest X-ray Images. Iraqi Journal of Computer, Communications and Control Engineering. 2022. Vol. 22, no. 3, pp.1-14.
https://search.emarefa.net/detail/BIM-1492769
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references : p. 13-14
Record ID
BIM-1492769