Artificial Intelligence Approaches on X‑ray‑oriented Images Process for Early Detection of COVID‑۱۹
عنوان مقاله: Artificial Intelligence Approaches on X‑ray‑oriented Images Process for Early Detection of COVID‑۱۹
شناسه ملی مقاله: JR_JMSI-12-3_006
منتشر شده در در سال 1401
شناسه ملی مقاله: JR_JMSI-12-3_006
منتشر شده در در سال 1401
مشخصات نویسندگان مقاله:
Sorayya Rezayi - Department of Health Information Management, School of Allied Medical Sciences, Tehran University of Medical Sciences, Tehran, Iran
Marjan Ghazisaeedi - Department of Health Information Management, School of Allied Medical Sciences, Tehran University of Medical Sciences, Tehran, Iran
Sharareh Rostam Niakan Kalhori - Department of Health Information Management, School of Allied Medical Sciences, Tehran University of Medical Sciences, Tehran, Iran
Soheila Saeedi - Department of Health Information Management, School of Allied Medical Sciences, Tehran University of Medical Sciences, Tehran, Iran- Clinical Research Development Unit of Farshchian Heart Center, Hamadan University of Medical Sciences, Hamadan, Iran
خلاصه مقاله:
Sorayya Rezayi - Department of Health Information Management, School of Allied Medical Sciences, Tehran University of Medical Sciences, Tehran, Iran
Marjan Ghazisaeedi - Department of Health Information Management, School of Allied Medical Sciences, Tehran University of Medical Sciences, Tehran, Iran
Sharareh Rostam Niakan Kalhori - Department of Health Information Management, School of Allied Medical Sciences, Tehran University of Medical Sciences, Tehran, Iran
Soheila Saeedi - Department of Health Information Management, School of Allied Medical Sciences, Tehran University of Medical Sciences, Tehran, Iran- Clinical Research Development Unit of Farshchian Heart Center, Hamadan University of Medical Sciences, Hamadan, Iran
Background: COVID-۱۹ 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-۱۹ 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 ۲۱ September ۲۰۲۰. Results: We
identified ۲۰۸ papers after duplicate removal and filtered them into ۶۰ citations based on inclusion
and exclusion criteria. Direct results sufficiently indicated a noticeable increase in the number of
published papers in July-۲۰۲۰. 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 ResNet۱۸ in reviewed techniques; all the mentioned indicators for this
mentioned network were equal to one (۱۰۰%). Conclusion: This review revealed that the application
of AI can accelerate the process of diagnosing COVID-۱۹, and these methods are effective for the
identification of COVID-۱۹ cases exploiting Chest X-ray images.
کلمات کلیدی: ۲۰۱۹‑nCoV disease, artificial intelligence, computed tomography, deep learning, image processing, X‑ray images
صفحه اختصاصی مقاله و دریافت فایل کامل: https://civilica.com/doc/1700828/