Exploring the Deep-Learning Techniques in Detecting the Presence of Coronavirus in the Chest X-Ray Images: A Comprehensive Review.
Exploring the Deep-Learning Techniques in Detecting the Presence of Coronavirus in the Chest X-Ray Images: A Comprehensive Review.
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DOI：
10.1007/s11831-022-09768-x
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发表时间：
2022
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影响因子：
--
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致命的冠状病毒（COVID-19）是影响整个世界的危险疾病之一，正在迅速传播疾病。这种传播可以通过在早期阶段发现和预防患者来减少。检测冠状病毒最常见的诊断工具是逆转录-聚合酶链反应（RT-PCR）测试，该测试耗时，还需要更多的设备和人力。此外，许多国家缺乏RT-PCR试剂盒。这就是为什么开发人工智能（AI）技术来检测冠状病毒的爆发是非常重要的。这促使许多研究人员使用X射线图像进行深度学习方法，以进行更具决定性的分析。因此，本文概述了许多使用传统和预先训练的深度学习方法的论文，这些方法是新开发的，用于减少COVID-19疾病的传播。具体而言，先进的深度学习方法在从胸部X射线图像中提取特征方面发挥着关键作用。然后，这些特征被用来分类患者是否受到冠状病毒的影响。此外，本文还表明深度学习技术在医学领域有可能应用。
The deadly coronavirus (COVID-19) is one of the dangerous diseases affecting the entire world and is fastly spreading disease. This spread can be reduced by detecting and quarantining the patients at an earlier stage. The most common diagnostic tool for detecting the coronavirus is the Reverse transcription-polymerase chain reaction (RT-PCR) test which is time-consuming and also needs more equipment and manpower. Furthermore, many countries had a deficit of RTPCR kits. This is why it is exceptionally very crucial to develop artificial intelligence (AI) techniques to detect the outbreak of coronavirus. This motivated many researchers to involve deep-learning methods using X-ray images for more decisive analysis. Thus, this paper outlines many papers that used traditional and pre-trained deep learning methods that are newly developed to reduce the spread of COVID-19 disease. Specifically, advanced deep learning methods play a critical role in extracting the features from the chest X-ray images. These features are then used to classify whether the patient is affected with coronavirus or not. Besides, this paper shows that deep learning techniques have probable applications in the medical field.
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DOI：
10.1080/07391102.2020.1767212
发表时间：
2020-05-21
影响因子：
4.4
作者：
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通讯作者：
Chawki, Youness
DOI：
10.1007/s11831-021-09641-3
发表时间：
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期刊：
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