Combining a convolutional neural network with autoencoders to predict the survival chance of COVID-19 patients
COVID-19 has caused many deaths worldwide. The automation of the diagnosis of this virus
is highly desired. Convolutional neural networks (CNNs) have shown outstanding …
is highly desired. Convolutional neural networks (CNNs) have shown outstanding …
Convolutional neural networks for the diagnosis and prognosis of the coronavirus disease pandemic
S Kugunavar, CJ Prabhakar - … computing for industry, biomedicine, and art, 2021 - Springer
A neural network is one of the current trends in deep learning, which is increasingly gaining
attention owing to its contribution in transforming the different facets of human life. It also …
attention owing to its contribution in transforming the different facets of human life. It also …
COVID-19 diagnosis using state-of-the-art CNN architecture features and Bayesian Optimization
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 …
affected the lives of millions of people and many people died from this infection. To prevent …
A deep learning prognosis model help alert for COVID-19 patients at high-risk of death: a multi-center study
Since its outbreak in December 2019, the persistent coronavirus disease (COVID-19)
became a global health emergency. It is imperative to develop a prognostic tool to identify …
became a global health emergency. It is imperative to develop a prognostic tool to identify …
A comprehensive study on classification of COVID-19 on computed tomography with pretrained convolutional neural networks
TD Pham - Scientific reports, 2020 - nature.com
The use of imaging data has been reported to be useful for rapid diagnosis of COVID-19.
Although computed tomography (CT) scans show a variety of signs caused by the viral …
Although computed tomography (CT) scans show a variety of signs caused by the viral …
Enhanced framework for COVID-19 prediction with computed tomography scan images using dense convolutional neural network and novel loss function
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 disease in patients. Several deep learning (DL) methods have been proposed for …
Deep convolutional neural network–based image classification for COVID-19 diagnosis
Initial cases of COVID-19 trace back to the end of 2019 which has laid foundations for the
extensive spread of the disease risking lives worldwide. In response to the global …
extensive spread of the disease risking lives worldwide. In response to the global …
A survey on deep learning in COVID-19 diagnosis
X Han, Z Hu, S Wang, Y Zhang - Journal of imaging, 2022 - mdpi.com
According to the World Health Organization statistics, as of 25 October 2022, there have
been 625,248,843 confirmed cases of COVID-19, including 65,622,281 deaths worldwide …
been 625,248,843 confirmed cases of COVID-19, including 65,622,281 deaths worldwide …
Deep insight: Convolutional neural network and its applications for COVID-19 prognosis
NY Khanday, SA Sofi - Biomedical Signal Processing and Control, 2021 - Elsevier
Background and objective SARS-CoV-2, a novel strain of coronavirus' also called
coronavirus disease 19 (COVID-19), a highly contagious pathogenic respiratory viral …
coronavirus disease 19 (COVID-19), a highly contagious pathogenic respiratory viral …
Neural Networks for the Detection of COVID-19 and Other Diseases: Prospects and Challenges
Artificial neural networks (ANNs) ability to learn, correct errors, and transform a large amount
of raw data into beneficial medical decisions for treatment and care has increased in …
of raw data into beneficial medical decisions for treatment and care has increased in …