论文标题
使用人工智能从胸部X射线图像中检测COVID-19
Detection of Covid-19 From Chest X-ray Images Using Artificial Intelligence: An Early Review
论文作者
论文摘要
2019年，由于新出现的冠状病毒（Covid-19），整个世界面临着健康紧急情况。几乎196个国家受到COVID-19的影响，而美国，意大利，中国，西班牙，伊朗和法国则是Covid-19的最大活跃案例。医疗和医疗部门的问题正面临延迟检测COVID-19的问题。几个基于人工智能的系统设计用于使用胸部X射线自动检测Covid-19。在本文中，我们将讨论用于检测Covid-19的不同方法以及我们面临的挑战。必须开发自动检测系统，以防止通过接触转移病毒。部署了几种深度学习架构，以检测Covid-19，例如重建，Inception，Googlenet等。所有这些方法都在检测到患有肺炎的受试者，而很难决定肺炎是由Covid-19引起的还是其他细菌或其他细菌攻击引起的。
In 2019, the entire world is facing a situation of health emergency due to a newly emerged coronavirus (COVID-19). Almost 196 countries are affected by covid-19, while USA, Italy, China, Spain, Iran, and France have the maximum active cases of COVID-19. The issues, medical and healthcare departments are facing in delay of detecting the COVID-19. Several artificial intelligence based system are designed for the automatic detection of COVID-19 using chest x-rays. In this article we will discuss the different approaches used for the detection of COVID-19 and the challenges we are facing. It is mandatory to develop an automatic detection system to prevent the transfer of the virus through contact. Several deep learning architecture are deployed for the detection of COVID-19 such as ResNet, Inception, Googlenet etc. All these approaches are detecting the subjects suffering with pneumonia while its hard to decide whether the pneumonia is caused by COVID-19 or due to any other bacterial or fungal attack.
