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      COVID-19 Diagnosis Using DWT And (2D)(2D)PCA From Chest X-Ray Image

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            Abstract

            COVID-19 is a respiratory disease, one that especially reaches into your respiratory tract, which includes your lungs.COVID-19 can cause a range of breathing problem, from mild to critical. Older adults and people who have other health conditions likeheart disease,cancer and diabetesmay have more serious symptoms.About 80% of people who have COVID-19 get Mild to moderate symptoms. You may have a drycough or a sore throat Some people have pneumonia, a lung infection in which the alveoli are inflamed.About 14% of COVID-19 cases are severe, with an infection that affects both lungs. As the swelling gets worse, your lungs fill with fluid and debris.You might also have more serious pneumonia. The air sacs fill withmucus, fluid, and other cells that are trying to fight the infection. This can make it harder for your body to take in oxygen. You may havetrouble breathingor feel short of breath. You may also breathe faster.If your doctor takes a CT scan of your chest, the opaque spots in your lungs look like they start to connect to each other.Approximation lungs Image (ALI) with Principal Component Analysis (2D) 2PCA (Two-Directional Two Dimension Principal Component Analysis) are applied for feature extraction, and SVM is used for classification. The experiments are conducted on a number of well-known face image databases taken in controlled (FERET, FEI, AR, and Extreme infection) as well as uncontrolled environment (LFW). The experimental analysis shows that the proposed approaches give an acceptable classification rate with reduced feature size.

            Content

            Author and article information

            Journal
            ScienceOpen Preprints
            ScienceOpen
            13 June 2022
            Affiliations
            [1 ] Department of computer science/Gyan Ganga Institute of Technology and Sciences/RGPV/P.O near Tilwara Ghat road Bargi hills Jabalpur
            Author notes
            Article
            10.14293/S2199-1006.1.SOR-.PP9JIQZ.v1
            e3885284-80da-49bd-a928-6815d5ae4435

            This work has been published open access under Creative Commons Attribution License CC BY 4.0 , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Conditions, terms of use and publishing policy can be found at www.scienceopen.com .


            Data sharing not applicable to this article as no datasets were generated or analysed during the current study.
            Computer science,Infectious disease & Microbiology
            Two Dimensional Principal component Analysis,COVID-19,Support Vector Machine,respiratory disease,Approximation lungs image

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