RETRACTED: COVID-19 image transmission using convolutional neural networks based algorithms for medical applications
ISSN: 1708-5284
Article publication date: 25 June 2021
Issue publication date: 15 March 2022
Retraction statement
The publishers of World Journal of Engineering wish to retract the article Ch, G., Ajay Nagendra, N., Aaqib, S.M., Sulaikha, C.M., Kv, S. and Santoshachandra Rao, K. (2022), “COVID-19 image transmission using convolutional neural networks based algorithms for medical applications”, World Journal of Engineering, Vol. 19 No. 2, pp. 183-188. https://doi.org/10.1108/WJE-03-2021-0158.
An internal investigation into a series of submissions has uncovered evidence that the peer review process was compromised. As a result of these concerns, the findings of the article cannot be relied upon. This decision has been taken in accordance with Emerald's publishing ethics and the COPE guidelines on retractions. The authors of this article would like to note that they do not agree with the content of this notice.
The publishers of the journal sincerely apologize to the readers.
Abstract
Purpose
COVID-19 would have a far-reaching impact on the international health-care industry and the patients. For COVID-19, there is a need for unique screening tests to reliably and rapidly determine who is infected. Medical COVID images protection is critical when data pertaining to computer images are being transmitted through public networks in health information systems.
Design/methodology/approach
Medical images such as computed tomography (CT) play key role in the diagnosis of COVID-19 patients. Neural networks-based methods are designed to detect COVID patients using chest CT scan images. And CT images are transmitted securely in health information systems.
Findings
The authors hereby examine neural networks-based COVID diagnosis methods using chest CT scan images and secure transmission of CT images for health information systems. For screening patients infected with COVID-19, a new approach using convolutional neural networks is proposed, and its output is simulated.
Originality/value
The required patient’s chest CT scan images have been taken from online databases such as GitHub. The experiments show that neural networks-based methods are effective in the diagnosis of COVID-19 patients using chest CT scan images.
Keywords
Citation
Ch, G., Ajay Nagendra, N., Aaqib, S.M., Sulaikha, C.M., Kv, S. and Santoshachandra Rao, K. (2022), "RETRACTED: COVID-19 image transmission using convolutional neural networks based algorithms for medical applications", World Journal of Engineering, Vol. 19 No. 2, pp. 183-188. https://doi.org/10.1108/WJE-03-2021-0158
Publisher
:Emerald Publishing Limited
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