Meta-analysis of predictions of COVID-19 disease based on CT-scan and X-ray images. Issue 2 (17th February 2021)

• Record Type: Journal Article
• Authors: Bhatt, Devershi Pallavi; Bhatnagar, Vaibhav; Sharma, Preeti
• Is Part Of: Journal of interdisciplinary mathematics. Volume 24:Issue 2(2021)
• Page Start: 381
• Page End: 409
• Publication Date: 2021-02-17
• Subjects: 62P10; COVID-19 -- Medical imaging -- Deep learning -- Meta-analysis -- CT scan -- X-Ray; Mathematics -- Periodicals; Mathematics; Periodicals; 510.5
• DOI: 10.1080/09720502.2021.1884385
• Languages: English
• ISSNs: 0972-0502

Abstract

Abstract: World is facing a pandemic from last few months entitled as COVID-19 caused by novel CORONA VIRUS. The outbreak of this disease started in year ending of 2019 from Wuhan, China and has affected almost all countries in the world. Till now, there is no vaccine for this disease however researchers are doing their best to find vaccine for the particular. Medical Imaging techniques are playing vital role in helping doctors to treat patients by giving detailed information about internal body parts of humans. The outbreak of COVID-19 has encouraged researchers to develop medical imaging-based solutions so that medical team can diagnose patients infected with COVID-19 in less time and required treatment can be started on time. X-ray and CT scan are two important techniques in field of medical imaging. Main objective of presented study is to perform meta-analysis of the studies that proposed neural network-based classification/segmentation models for diagnosing COVID-19 disease on CT scan or X-rays. Meta-analysis has been performed on 35 studies on X-ray and 35 studies on CT-scan images for prediction of COVID-19. Analysis suggests that there is heterogeneity in publications to predict the COVID-19 disease on CT scans and X-rays using deep learning models. However, no publication biasness is found in both the studies.