Automated detection and forecasting of covid-19 using deep learning techniques: A review
Abstract In March 2020, the World Health Organization (WHO) declared COVID-19 a global
epidemic, caused by the SARS-CoV-2 virus. Initially, COVID-19 was diagnosed using real …
epidemic, caused by the SARS-CoV-2 virus. Initially, COVID-19 was diagnosed using real …
Applications of artificial intelligence in battling against covid-19: A literature review
M Tayarani - Chaos, Solitons and Fractals, 2020 - researchprofiles.herts.ac.uk
Colloquially known as coronavirus, the Severe Acute Respiratory Syndrome CoronaVirus 2
(SARS-CoV-2), that causes CoronaVirus Disease 2019 (COVID-19), has become a matter of …
(SARS-CoV-2), that causes CoronaVirus Disease 2019 (COVID-19), has become a matter of …
[HTML][HTML] Comparative analysis of Gated Recurrent Units (GRU), long Short-Term memory (LSTM) cells, autoregressive Integrated moving average (ARIMA), seasonal …
Several machine learning and deep learning models were reported in the literature to
forecast COVID-19 but there is no comprehensive report on the comparison between …
forecast COVID-19 but there is no comprehensive report on the comparison between …
Forecasting the dynamics of cumulative COVID-19 cases (confirmed, recovered and deaths) for top-16 countries using statistical machine learning models: Auto …
Most countries are reopening or considering lifting the stringent prevention policies such as
lockdowns, consequently, daily coronavirus disease (COVID-19) cases (confirmed …
lockdowns, consequently, daily coronavirus disease (COVID-19) cases (confirmed …
Forecasting of COVID-19 using deep layer recurrent neural networks (RNNs) with gated recurrent units (GRUs) and long short-term memory (LSTM) cells
In December 2019, first case of the COVID-19 was reported in Wuhan, Hubei province in
China. Soon world health organization has declared contagious coronavirus disease (aka …
China. Soon world health organization has declared contagious coronavirus disease (aka …
Time series prediction for the epidemic trends of COVID-19 using the improved LSTM deep learning method: Case studies in Russia, Peru and Iran
P Wang, X Zheng, G Ai, D Liu, B Zhu - Chaos, Solitons & Fractals, 2020 - Elsevier
The COVID-19 outbreak in late December 2019 is still spreading rapidly in many countries
and regions around the world. It is thus urgent to predict the development and spread of the …
and regions around the world. It is thus urgent to predict the development and spread of the …
Time series predicting of COVID-19 based on deep learning
COVID-19 was declared a global pandemic by the World Health Organisation (WHO) on
11th March 2020. Many researchers have, in the past, attempted to predict a COVID …
11th March 2020. Many researchers have, in the past, attempted to predict a COVID …
Sociodemographic determinants of COVID-19 incidence rates in Oman: Geospatial modelling using multiscale geographically weighted regression (MGWR)
S Mansour, A Al Kindi, A Al-Said, A Al-Said… - Sustainable cities and …, 2021 - Elsevier
The current COVID-19 pandemic is evolving rapidly into one of the most devastating public
health crises in recent history. By mid-July 2020, reported cases exceeded 13 million …
health crises in recent history. By mid-July 2020, reported cases exceeded 13 million …
An approach to forecast impact of Covid‐19 using supervised machine learning model
S Mohan, A Abugabah, S Kumar Singh… - Software: Practice …, 2022 - Wiley Online Library
The Covid‐19 pandemic has emerged as one of the most disquieting worldwide public
health emergencies of the 21st century and has thrown into sharp relief, among other …
health emergencies of the 21st century and has thrown into sharp relief, among other …
Development of sustainable and resilient healthcare and non-cold pharmaceutical distribution supply chain for COVID-19 pandemic: a case study
O Abdolazimi, M Salehi Esfandarani… - … International Journal of …, 2023 - emerald.com
Purpose This study evaluated the influence of the coronavirus pandemic on the healthcare
and non-cold pharmaceutical care distribution supply chain. Design/methodology/approach …
and non-cold pharmaceutical care distribution supply chain. Design/methodology/approach …