Search Results for author:
Found 2 papers, 1 papers with code
Simulation and application of COVID-19 compartment model using physics-informed neural network
COVID-19 pandemic has had a disruptive and irreversible impact globally, yet traditional epidemiological modeling approaches such as the susceptible-infected-recovered (SIR) model have exhibited limited effectiveness in forecasting of the up-to-date pandemic situation.
COVID-19 Pneumonia and Influenza Pneumonia Detection Using Convolutional Neural Networks
The chest radiograph appearance of COVID-19 pneumonia is thought to be nonspecific, having presented a challenge to identify an optimal architecture of a convolutional neural network (CNN) that would classify with a high sensitivity among the pulmonary inflammation features of COVID-19 and non-COVID-19 types of pneumonia.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
