Version 1
: Received: 29 March 2023 / Approved: 3 April 2023 / Online: 3 April 2023 (08:40:11 CEST)
How to cite:
Majhi, V.; Paul, S. Comparative Analysis on Available Technique for the Detection of Covid-19 through CT-Scan and X-Ray using Machine Learning: A Systematic Review. Preprints2023, 2023040019. https://doi.org/10.20944/preprints202304.0019.v1
Majhi, V.; Paul, S. Comparative Analysis on Available Technique for the Detection of Covid-19 through CT-Scan and X-Ray using Machine Learning: A Systematic Review. Preprints 2023, 2023040019. https://doi.org/10.20944/preprints202304.0019.v1
Majhi, V.; Paul, S. Comparative Analysis on Available Technique for the Detection of Covid-19 through CT-Scan and X-Ray using Machine Learning: A Systematic Review. Preprints2023, 2023040019. https://doi.org/10.20944/preprints202304.0019.v1
APA Style
Majhi, V., & Paul, S. (2023). Comparative Analysis on Available Technique for the Detection of Covid-19 through CT-Scan and X-Ray using Machine Learning: A Systematic Review. Preprints. https://doi.org/10.20944/preprints202304.0019.v1
Chicago/Turabian Style
Majhi, V. and Sudip Paul. 2023 "Comparative Analysis on Available Technique for the Detection of Covid-19 through CT-Scan and X-Ray using Machine Learning: A Systematic Review" Preprints. https://doi.org/10.20944/preprints202304.0019.v1
Abstract
(1) Background: In the year of 2020 Covid-19 was declared epidemic by WHO. From that time millions of people were affected and died by this disease. The main detection process for this epidemic is RT-PCR test or reverse polymerase transcription chain reaction test. One of the reason of spreading of this disease so much is lack of efficiency in RT-PCR test. Sampling error and low viral load were two main reasons for what the testing process faced such problems. Lung infection is a very common symptom for covid-19 patients, so, CT scan and chest X-ray imaging technique can be applied to detect patient at a very early stage of infection. Which will be very effective and also can be a better option to RT-PCR test; (2) Methods: We searched data in Scopus for articles published between 2020 and 2023. The initial set of articles was 189, from which 21 articles will eventually be selected by exclusion criteria; (3) Results: A total of thirteen (61.90%) articles were found working on detecting Covid-19 by extracting the X-ray and CT scan data individually. Three (14.28%) of those articles focused on a hybrid model of CT scan and X-ray Image Data. Another four articles made a comparison between Covid-19, pneumonia and a normal person to identify a Covid-19 patient. Where others have worked on unsupervised learning methods or SVM to detect Covid-19.; (4) Conclusions: We have conducted a systematic review of the studies that have been published up to this time, with the purpose to present a summary of the evidence about the detection of COVID-19. In this article, we have summarized and critically reviewed literatures which worked on development or application or both of different AI or ML technique from chest CT and X-ray images to find a solution to detect covid-19.
Keywords
Covid-19; Deep Learning; Computerized Tomography; Artificial Intelligence; Machine Learning; X-ray
Subject
Medicine and Pharmacology, Pulmonary and Respiratory Medicine
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
