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Journal of Medical Signals and Sensors، جلد ۱۲، شماره ۳، صفحات ۲۳۳-۲۵۳
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عنوان انگلیسی Artificial intelligence approaches on X-ray-oriented images process for early detection of COVID-19
چکیده انگلیسی مقاله 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.
کلیدواژه‌های انگلیسی مقاله 2019-nCoV disease, artificial intelligence, computed tomography, deep learning, image processing, X-ray images
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نشانی اینترنتی http://jmss.mui.ac.ir/index.php/jmss/article/view/626
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زبان مقاله منتشر شده en
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نوع مقاله منتشر شده Review Articles
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