Deep Learning-Based COVID-19 Detection Using CT and X-Ray Images: Current Analytics and Comparisons

Amjad Rehman, Tanzila Saba, Usman Tariq, Noor Ayesha

Research output: Contribution to journalArticlepeer-review

53 Scopus citations

Abstract

Currently, the world faces a novel coronavirus disease 2019 (COVID-19) challenge and infected cases are increasing exponentially. COVID-19 is a disease that has been reported by the WHO in March 2020, caused by a virus called the SARS-CoV-2. As of 10 March 2021, more than 150 million people were infected and 3v million died. Researchers strive to find out about the virus and recommend effective actions. An unprecedented increase in pathogens is happening and a major attempt is being made to tackle the epidemic. This article presents deep learning-based COVID-19 detection using CT and X-ray images and data analytics on its spread worldwide. This article's research structure builds on a recent analysis of the COVID-19 data and prospective research to systematize current resources, help the researchers, practitioners by using in-depth learning methodologies to build solutions for the COVID-19 pandemic.

Original languageEnglish
Article number9464121
Pages (from-to)63-68
Number of pages6
JournalIT Professional
Volume23
Issue number3
DOIs
StatePublished - 1 May 2021

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