论文标题
COVID-19使用残留注意网络进行筛选一种人工智能方法
COVID-19 Screening Using Residual Attention Network an Artificial Intelligence Approach
论文作者
论文摘要
冠状病毒疾病2019（COVID-19）是由严重的急性呼吸综合症冠状病毒2病毒（SARS-COV-2）引起的。该病毒迅速传播；它的基本生殖数为2.2-2.7。 2020年3月，世界卫生组织宣布Covid-19爆发是大流行。 Covid-19目前正在影响200多个活跃病例的国家。 COVID-19的有效测试策略对于控制爆发至关重要，但是对测试的需求超过了使用反转录聚合酶链反应（RT-PCR）的测试试剂盒的可用性。在本文中，我们提出了一种使用人工智能筛选Covid-19的技术。我们的技术仅需几秒钟即可筛选患者在患者中的存在。我们收集了一个胸部X射线图像的数据集，并训练了几个流行的深卷卷卷网络模型（VGG，Mobilenet，Xpection，Densenet，IntectionResnet），以对胸部X射线进行分类。然后，我们对这些模型不满意，然后设计并建立了一个残留的注意网络，该网络能够以98％的测试精度筛选Covid-19，验证精度为100％。我们的模型的特征地图显示了胸部X射线中的区域，这对于分类很重要。我们的工作可以帮助增加临床实践中AI辅助应用的适应。该项目中使用的代码和数据集可在https://github.com/vishalshar/covid-19-screening-using-ran-on-on-x-ray-images上找到。
Coronavirus Disease 2019 (COVID-19) is caused by severe acute respiratory syndrome coronavirus 2 virus (SARS-CoV-2). The virus transmits rapidly; it has a basic reproductive number R of 2.2-2.7. In March 2020, the World Health Organization declared the COVID-19 outbreak a pandemic. COVID-19 is currently affecting more than 200 countries with 6M active cases. An effective testing strategy for COVID-19 is crucial to controlling the outbreak but the demand for testing surpasses the availability of test kits that use Reverse Transcription Polymerase Chain Reaction (RT-PCR). In this paper, we present a technique to screen for COVID-19 using artificial intelligence. Our technique takes only seconds to screen for the presence of the virus in a patient. We collected a dataset of chest X-ray images and trained several popular deep convolution neural network-based models (VGG, MobileNet, Xception, DenseNet, InceptionResNet) to classify the chest X-rays. Unsatisfied with these models, we then designed and built a Residual Attention Network that was able to screen COVID-19 with a testing accuracy of 98% and a validation accuracy of 100%. A feature maps visual of our model show areas in a chest X-ray which are important for classification. Our work can help to increase the adaptation of AI-assisted applications in clinical practice. The code and dataset used in this project are available at https://github.com/vishalshar/covid-19-screening-using-RAN-on-X-ray-images.
