Hasani Sharif, Nasiri Hamid
Electrical and Computer Engineering Department, Semnan University, Semnan, Iran.
Department of Computer Engineering, Amirkabir University of Technology, Tehran, Iran.
Softw Impacts. 2022 Feb;11:100210. doi: 10.1016/j.simpa.2021.100210. Epub 2021 Dec 29.
Following the COVID-19 pandemic, scientists have been looking for different ways to diagnose COVID-19, and these efforts have led to a variety of solutions. One of the common methods of detecting infected people is chest radiography. In this paper, an Automated Detection System using X-ray images (COV-ADSX) is proposed, which employs a deep neural network and XGBoost to detect COVID-19. COV-ADSX was implemented using the Django web framework, which allows the user to upload an X-ray image and view the results of the COVID-19 detection and image's heatmap, which helps the expert to evaluate the chest area more accurately.
在新冠疫情之后，科学家们一直在寻找不同的方法来诊断新冠病毒，这些努力带来了各种各样的解决方案。检测感染者的常见方法之一是胸部X光检查。本文提出了一种使用X光图像的自动检测系统（COV-ADSX），该系统采用深度神经网络和XGBoost来检测新冠病毒。COV-ADSX是使用Django网络框架实现的，它允许用户上传X光图像并查看新冠病毒检测结果和图像的热图，这有助于专家更准确地评估胸部区域。
