NAGNN: classification of COVID‐19 based on neighboring aware representation from deep graph neural network
COVID‐19 pneumonia started in December 2019 and caused large casualties and huge
economic losses. In this study, we intended to develop a computer‐aided diagnosis system …
economic losses. In this study, we intended to develop a computer‐aided diagnosis system …
Covid-19 classification by FGCNet with deep feature fusion from graph convolutional network and convolutional neural network
SH Wang, VV Govindaraj, JM Górriz, X Zhang… - Information …, 2021 - Elsevier
Abstract (Aim) COVID-19 is an infectious disease spreading to the world this year. In this
study, we plan to develop an artificial intelligence based tool to diagnose on chest CT …
study, we plan to develop an artificial intelligence based tool to diagnose on chest CT …
Retracted article: Graphcovidnet: A graph neural network based model for detecting COVID-19 from ct scans and x-rays of chest
P Saha, D Mukherjee, PK Singh, A Ahmadian… - Scientific reports, 2021 - nature.com
COVID-19, a viral infection originated from Wuhan, China has spread across the world and it
has currently affected over 115 million people. Although vaccination process has already …
has currently affected over 115 million people. Although vaccination process has already …
An ensemble of global and local-attention based convolutional neural networks for COVID-19 diagnosis on chest X-ray images
The recent Coronavirus Disease 2019 (COVID-19) pandemic has put a tremendous burden
on global health systems. Medical practitioners are under great pressure for reliable …
on global health systems. Medical practitioners are under great pressure for reliable …
ResGNet-C: A graph convolutional neural network for detection of COVID-19
The widely spreading COVID-19 has caused thousands of hundreds of mortalities over the
world in the past few months. Early diagnosis of the virus is of great significance for both of …
world in the past few months. Early diagnosis of the virus is of great significance for both of …
COVID-19 classification by CCSHNet with deep fusion using transfer learning and discriminant correlation analysis
Aim: COVID-19 is a disease caused by a new strain of coronavirus. Up to 18th October
2020, worldwide there have been 39.6 million confirmed cases resulting in more than 1.1 …
2020, worldwide there have been 39.6 million confirmed cases resulting in more than 1.1 …
CGNet: A graph-knowledge embedded convolutional neural network for detection of pneumonia
X Yu, SH Wang, YD Zhang - Information Processing & Management, 2021 - Elsevier
Pneumonia is a global disease that causes high children mortality. The situation has even
been worsening by the outbreak of the new coronavirus named COVID-19, which has killed …
been worsening by the outbreak of the new coronavirus named COVID-19, which has killed …
CNN–RNN network integration for the diagnosis of COVID-19 using chest X-ray and CT images
The 2019 coronavirus disease (COVID-19) has rapidly spread across the globe. It is crucial
to identify positive cases as rapidly as humanely possible to provide appropriate treatment …
to identify positive cases as rapidly as humanely possible to provide appropriate treatment …
Covid-MANet: Multi-task attention network for explainable diagnosis and severity assessment of COVID-19 from CXR images
The devastating outbreak of Coronavirus Disease (COVID-19) cases in early 2020 led the
world to face health crises. Subsequently, the exponential reproduction rate of COVID-19 …
world to face health crises. Subsequently, the exponential reproduction rate of COVID-19 …
CGENet: a deep graph model for COVID-19 detection based on chest CT
Simple Summary This study proposes a new COVID-19 detection system called CGENet,
based on computer vision and chest computed tomography images. First, an optimal …
based on computer vision and chest computed tomography images. First, an optimal …