A Deep Neural Network for Detecting Coronavirus Disease Using Chest X-Ray Images

Rajeev Kumar Gupta, Nilesh Kunhare, Rajesh Kumar Pateriya and Nikhlesh Pathik
Additional contact information
Rajeev Kumar Gupta: Pandit Deendayal Energy University, Gandhinagar, India
Nilesh Kunhare: Amity University, India
Rajesh Kumar Pateriya: Maulana Azad National Institute Technology, India
Nikhlesh Pathik: Sagar Institute of Science and Technology, India

International Journal of Healthcare Information Systems and Informatics (IJHISI), 2022, vol. 17, issue 2, 1-27

Abstract: The novel Covid-19 is one of the leading cause of death worldwide in the year 2020 and declared as a pandemic by world health organization (WHO). This virus affecting all countries across the world and 5 lakh people die as of June 2020 due to Covid-19. Due to the highly contagious nature, early detection of this virus plays a vital role to break Covid chain. Recent studies done by China says that chest CT and X-Ray image may be used as a preliminary test for Covid detection. Deep learning-based CNN model can use to detect Coronavirus automatically from the chest X-rays images. This paper proposed a transfer learning-based approach to detect Covid disease. Due to the less number of Covid chest images, we are using a pre-trained model to classify X-ray images into Covid and Normal class. This paper presents the comparative study of a various pre-trained model like VGGNet-19, ResNet50 and Inception_ResNet_V2. Experiment results show that Inception_ResNet_V2 gives the better result as compare to VGGNet and ResNet model with training and test accuracy of 99.26 and 94, respectively.

Date: 2022
References: View complete reference list from CitEc
Citations:

Downloads: (external link)
http://services.igi-global.com/resolvedoi/resolve. ... /IJHISI.20220401.oa1 (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:igg:jhisi0:v:17:y:2022:i:2:p:1-27

Access Statistics for this article

International Journal of Healthcare Information Systems and Informatics (IJHISI) is currently edited by Qiang (Shawn) Cheng

More articles in International Journal of Healthcare Information Systems and Informatics (IJHISI) from IGI Global
Bibliographic data for series maintained by Journal Editor ().