Application of machine learning and medical imaging in the detection of COVID-19 patients: A review article
Accessinfo:eu-repo/semantics/openAccessAttribution-NonCommercial-ShareAlike 4.0 Internationalhttps://creativecommons.org/licenses/by-nc-sa/4.0/
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CitationYadollahi, S., Yadollahi, S., Zanjani, E. ve Khaleghi, F. (2022). Application of machine learning and medical imaging in the detection of COVID-19 patients: A review article. Journal of Family Medicine and Primary Care, 11(6), 2277-2283. http://doi.org/10.4103/jfmpc.jfmpc_1715_21
In the present study, a particular technique of artificial intelligence (AI) is applied for diagnosis and classifying medical images of patients with coronavirus disease (COVID-19). Chest radiography and laboratory-based tests are two of the most important diagnostic approaches for the detection of people with the coronavirus. Recently, a lot of studies have been carried out on using AI techniques for achieving appropriate diagnosis of COVID-19 patients using computed tomography (CT) of the chest. The present study is reviewing all available literature that have investigated the role of chest CT toward AI in the detection of COVID-19. As a novel field of computer science, AI focuses on teaching computers to be capable of learning complex tasks and decide about their solution methods. in this study, we used Matlab, Payton, and Fortran software as well as other software which are suitable for this research. In this regard, the present review study is aimed to collect the information from all the studies conducted on the role of AI as a decisive and comprehensive technology for the detection of coronavirus in patients to have a more accurate diagnosis and investigate its epidemiology.