COVID‐19 disease severity assessment using CNN model

E Irmak - IET image processing, 2021 - Wiley Online Library
Due to the highly infectious nature of the novel coronavirus (COVID‐19) disease, excessive
number of patients waits in the line for chest X‐ray examination, which overloads the …

CoVNet-19: A Deep Learning model for the detection and analysis of COVID-19 patients

P Kedia, R Katarya - Applied Soft Computing, 2021 - Elsevier
Background: The ongoing fight with Novel Corona Virus, getting quick treatment, and rapid
diagnosis reports have become an act of high priority. With millions getting infected daily …

A novel fusion based convolutional neural network approach for classification of COVID-19 from chest X-ray images

A Sharma, K Singh, D Koundal - Biomedical Signal Processing and Control, 2022 - Elsevier
Coronavirus disease is a viral infection caused by a novel coronavirus (CoV) which was first
identified in the city of Wuhan, China somewhere in the early December 2019. It affects the …

[HTML][HTML] COVINet: A hybrid model for classification of COVID and non-COVID pneumonia in CT and X-Ray imagery

V Mittal, A Kumar - International Journal of Cognitive Computing in …, 2023 - Elsevier
The COVID-19 pandemic has resulted in a significant increase in the number of pneumonia
cases, including those caused by the Coronavirus. To detect COVID pneumonia, RT-PCR is …

COVID-19 classification in X-ray chest images using a new convolutional neural network: CNN-COVID

PM De Sousa, PC Carneiro, MM Oliveira… - Research on Biomedical …, 2021 - Springer
Purpose COVID-19 causes lung inflammation and lesions, and chest X-ray and computed
tomography images are remarkably suitable for differentiating the new disease from patients …

A light-weight convolutional Neural Network Architecture for classification of COVID-19 chest X-Ray images

M Masud - Multimedia systems, 2022 - Springer
The COVID-19 pandemic has opened numerous challenges for scientists to use massive
data to develop an automatic diagnostic tool for COVID-19. Since the outbreak in January …

Enhanced framework for COVID-19 prediction with computed tomography scan images using dense convolutional neural network and novel loss function

A Motwani, PK Shukla, M Pawar, M Kumar… - Computers and …, 2023 - Elsevier
Recent studies have shown that computed tomography (CT) scan images can characterize
COVID-19 disease in patients. Several deep learning (DL) methods have been proposed for …

COVID-19 chest X-ray classification and severity assessment using convolutional and transformer neural networks

T Le Dinh, SH Lee, SG Kwon, KR Kwon - Applied Sciences, 2022 - mdpi.com
The coronavirus pandemic started in Wuhan, China in December 2019, and put millions of
people in a difficult situation. This fatal virus spread to over 227 countries and the number of …

COVINet: a convolutional neural network approach for predicting COVID-19 from chest X-ray images

M Umer, I Ashraf, S Ullah, A Mehmood… - Journal of Ambient …, 2022 - Springer
COVID-19 pandemic is widely spreading over the entire world and has established
significant community spread. Fostering a prediction system can help prepare the officials to …

COVID-19 diagnosis using state-of-the-art CNN architecture features and Bayesian Optimization

MF Aslan, K Sabanci, A Durdu, MF Unlersen - Computers in biology and …, 2022 - Elsevier
The coronavirus outbreak 2019, called COVID-19, which originated in Wuhan, negatively
affected the lives of millions of people and many people died from this infection. To prevent …