Diagnosing COVID-19 Infection in Chest X-Ray Images Using Neural Network

With its rapid spread, the coronavirus infection shocked the world and had a huge effect on billions of peoples' lives. The problem is to find a safe method to diagnose the infections with fewer casualties. It has been shown that X-Ray images are an important method for the identification, qua...

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Bibliographic Details
Main Authors: Salim M. Zaki, Mustafa Musa Jaber, Mohammed A. Kashmoola
Format: Article
Language:English
Published: University of Baghdad, College of Science for Women 2022-12-01
Series:مجلة بغداد للعلوم
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Online Access:https://bsj.uobaghdad.edu.iq/index.php/BSJ/article/view/5965
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Summary:With its rapid spread, the coronavirus infection shocked the world and had a huge effect on billions of peoples' lives. The problem is to find a safe method to diagnose the infections with fewer casualties. It has been shown that X-Ray images are an important method for the identification, quantification, and monitoring of diseases. Deep learning algorithms can be utilized to help analyze potentially huge numbers of X-Ray examinations. This research conducted a retrospective multi-test analysis system to detect suspicious COVID-19 performance, and use of chest X-Ray features to assess the progress of the illness in each patient, resulting in a "corona score." where the results were satisfactory compared to the benchmarked techniques.  This research results showed that rapidly evolved Artificial Intelligence (AI) -based image analysis can accomplish high accuracy in detecting coronavirus infection as well as quantification and illness burden monitoring.
ISSN:2078-8665
2411-7986