Journal of Medical Signals & Sensors

REVIEW ARTICLE
Year
: 2022  |  Volume : 12  |  Issue : 3  |  Page : 233--253

Artificial intelligence approaches on X-ray-oriented images process for early detection of COVID-19


Sorayya Rezayi1, Marjan Ghazisaeedi1, Sharareh Rostam Niakan Kalhori1, Soheila Saeedi2 
1 Department of Health Information Management, School of Allied Medical Sciences, Tehran University of Medical Sciences, Tehran, Iran
2 Department of Health Information Management, School of Allied Medical Sciences, Tehran University of Medical Sciences, Tehran; Clinical Research Development Unit of Farshchian Heart Center, Hamadan University of Medical Sciences, Hamadan, Iran

Correspondence Address:
Soheila Saeedi
Department of Health Information Management, 3rd Floor, School of Allied Medical Sciences, Tehran University of Medical Sciences, No #17, Farredanesh Alley, Ghods St., Enghelab Ave., Postal Code: 14177-44361, Tehran
Iran

Background: COVID-19 is a global public health problem that is crucially important to be diagnosed in the early stages. This study aimed to investigate the use of artificial intelligence (AI) to process X-ray-oriented images to diagnose COVID-19 disease. Methods: A systematic search was conducted in Medline (through PubMed), Scopus, ISI Web of Science, Cochrane Library, and IEEE Xplore Digital Library to identify relevant studies published until 21 September 2020. Results: We identified 208 papers after duplicate removal and filtered them into 60 citations based on inclusion and exclusion criteria. Direct results sufficiently indicated a noticeable increase in the number of published papers in July-2020. The most widely used datasets were, respectively, GitHub repository, hospital-oriented datasets, and Kaggle repository. The Keras library, Tensorflow, and Python had been also widely employed in articles. X-ray images were applied more in the selected articles. The most considerable value of accuracy, sensitivity, specificity, and Area under the ROC Curve was reported for ResNet18 in reviewed techniques; all the mentioned indicators for this mentioned network were equal to one (100%). Conclusion: This review revealed that the application of AI can accelerate the process of diagnosing COVID-19, and these methods are effective for the identification of COVID-19 cases exploiting Chest X-ray images.


How to cite this article:
Rezayi S, Ghazisaeedi M, Kalhori SR, Saeedi S. Artificial intelligence approaches on X-ray-oriented images process for early detection of COVID-19.J Med Signals Sens 2022;12:233-253


How to cite this URL:
Rezayi S, Ghazisaeedi M, Kalhori SR, Saeedi S. Artificial intelligence approaches on X-ray-oriented images process for early detection of COVID-19. J Med Signals Sens [serial online] 2022 [cited 2023 Feb 9 ];12:233-253
Available from: https://www.jmssjournal.net/article.asp?issn=2228-7477;year=2022;volume=12;issue=3;spage=233;epage=253;aulast=Rezayi;type=0