[HTML][HTML] Application of artificial neural networks to predict the COVID-19 outbreak
HR Niazkar, M Niazkar - Global Health Research and Policy, 2020 - Springer
Background Millions of people have been infected worldwide in the COVID-19 pandemic. In
this study, we aim to propose fourteen prediction models based on artificial neural networks …
this study, we aim to propose fourteen prediction models based on artificial neural networks …
[HTML][HTML] A predictive analytics model for COVID-19 pandemic using artificial neural networks
The COVID-19 pandemic spread rapidly around the world and is currently one of the most
leading causes of death and heath disaster in the world. Turkey, like most of the countries …
leading causes of death and heath disaster in the world. Turkey, like most of the countries …
[HTML][HTML] Exponentially increasing trend of infected patients with COVID-19 in Iran: a comparison of neural network and ARIMA forecasting models
L Moftakhar, S Mozhgan, MS Safe - Iranian Journal of Public …, 2020 - ncbi.nlm.nih.gov
Background: The outbreak of COVID-19 is rapidly spreading around the world and became
a pandemic disease. For help to better planning of interventions, this study was conducted to …
a pandemic disease. For help to better planning of interventions, this study was conducted to …
[HTML][HTML] Artificial neural network and logistic regression modelling to characterize COVID-19 infected patients in local areas of Iran
F Mohammadi, H Pourzamani, H Karimi… - Biomedical journal, 2021 - Elsevier
Background COVID-19 is an infectious disease that started spreading globally at the end of
2019. Due to differences in patient characteristics and symptoms in different regions, in this …
2019. Due to differences in patient characteristics and symptoms in different regions, in this …
[HTML][HTML] Application of machine learning in the prediction of COVID-19 daily new cases: A scoping review
COVID-19 has produced a global pandemic affecting all over of the world. Prediction of the
rate of COVID-19 spread and modeling of its course have critical impact on both health …
rate of COVID-19 spread and modeling of its course have critical impact on both health …
[HTML][HTML] Forecasting COVID-19 new cases using deep learning methods
L Xu, R Magar, AB Farimani - Computers in biology and medicine, 2022 - Elsevier
After nearly two years since the first identification of SARS-CoV-2 virus, the surge in cases
because of virus mutations is a cause of grave public health concern across the globe. As a …
because of virus mutations is a cause of grave public health concern across the globe. As a …
[HTML][HTML] Predicting the epidemic curve of the coronavirus (SARS-CoV-2) disease (COVID-19) using artificial intelligence: An application on the first and second waves
Objectives The COVID-19 pandemic is considered a major threat to global public health.
The aim of our study was to use the official epidemiological data to forecast the epidemic …
The aim of our study was to use the official epidemiological data to forecast the epidemic …
[HTML][HTML] COVID-19 prevalence forecasting using autoregressive integrated moving average (ARIMA) and artificial neural networks (ANN): case of Turkey
A local outbreak of unknown pneumonia was detected in Wuhan (Hubei, China) in
December 2019. It is determined to be caused by a severe acute respiratory syndrome …
December 2019. It is determined to be caused by a severe acute respiratory syndrome …
Forecasting the prevalence of COVID-19 outbreak in Egypt using nonlinear autoregressive artificial neural networks
AI Saba, AH Elsheikh - Process safety and environmental protection, 2020 - Elsevier
Abstract SARS-CoV-2 (COVID-19) is a new Coronavirus, with first reported human infections
in late 2019. COVID-19 has been officially declared as a universal pandemic by the World …
in late 2019. COVID-19 has been officially declared as a universal pandemic by the World …
COVID‐19 in Iran: forecasting pandemic using deep learning
COVID‐19 has led to a pandemic, affecting almost all countries in a few months. In this work,
we applied selected deep learning models including multilayer perceptron, random forest …
we applied selected deep learning models including multilayer perceptron, random forest …