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Diagnostic COVID-19 based on chest imaging of COVID-19: A survey | ||
| International Journal of Nonlinear Analysis and Applications | ||
| مقاله 100، دوره 14، شماره 1، فروردین 2023، صفحه 1295-1309 اصل مقاله (983.23 K) | ||
| نوع مقاله: Research Paper | ||
| شناسه دیجیتال (DOI): 10.22075/ijnaa.2022.6987 | ||
| نویسندگان | ||
| Saja Ali Ayyed* ؛ Alyaa Al-Barrak | ||
| Department of Computer Science, College of Science, University of Baghdad, Baghdad, Iraq | ||
| تاریخ دریافت: 19 تیر 1401، تاریخ بازنگری: 26 مرداد 1401، تاریخ پذیرش: 07 مهر 1401 | ||
| چکیده | ||
| As of June 24, 2020, the coronavirus infection (COVID-19) has infected more than 9.3 million people and resulted in more than 0.47 million deaths globally. COVID-19 cannot be diagnosed or treated without chest imaging procedures such as computed tomography and X-rays. Due to the highly infectious nature of this disease, radiologists are under continual pressure to diagnose and treat patients. As a possible solution to these issues and to enhance diagnostic accuracy, artificial intelligence (AI)-based image analysis techniques are being investigated. This assessment focuses on the present state of chest imaging analysis techniques using artificial intelligence for COVID-19. Note in particular the imaging analysis methodologies of two common viral types of pneumonia that may be used as a reference for assessing the illness utilizing chest pictures. Examine in deeper depth the progress of AI-assisted illness diagnosis and assessment, finding that AI approaches in this application are extremely useful. Focus on the role of artificial intelligence in the Corona epidemic and analyze the feme dataset utilized in prior studies as well as any relevant articles. | ||
| کلیدواژهها | ||
| COVID-19؛ artificial intelligence (AI)؛ Chest imaging؛ dataset | ||
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