COVID-19 Demystified based on Chest X-Ray

Abstract

The repercussions of a global pandemic were observed in 2019 as a COVID-19 that spread whole over the world. SARS-CoV-2, an acronym for Severe Acute Respiratory Syndrome Coronavirus 2, is the beta coronavirus accountable for the disease. The enormous number of fatalities and afflicted people throughout the world provide insight into the disease’s severity. The condition can be better managed if the diagnosis is made quickly. Diagnostic laboratory tests are accessible, however they are constrained by the time available and the testing kits that are available. The manual testing of coronavirus in the beginning made it impossible to handle the rising number of COVID - 19 effectively. The coronavirus is also classified into 3 stages, each of which affects the lungs in a distinct way. In order to deal with this scenario, researchers have tried to use artificial intelligence technologies to identify coronavirus utilizing Chest X-Ray and CT scan pictures. AI plays a crucial role in forecasting coronavirus cases by analyzing the virus’s structural composition, while Chest X-Ray with CT scan images assist in identifying the stages of the virus. Utilizing deep convolutional neural networks (DCNN), COVID-19 pneumonia patients can be automatically recognized in digital Chest X-Ray images, ensuring maximum detection accuracy. This study evaluates over 50 publications spanning from 2020 to 2022. Adolescents in India express significant impacts on various aspects of their lives due to the pandemic, particularly expressing concerns about their physical health, social and recreational activities, and academic performance. These findings underscore the importance of accessible digital healthcare and education provisions. The study’s conclusions encompass the assessment of algorithms and techniques applied to a specific research problem, highlighting their strengths and weaknesses, along with potential avenues for further research in the field.

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