Artificial intelligence for forecasting and diagnosing COVID-19 pandemic: A focused review
The outbreak of novel corona virus 2019 (COVID-19) has been treated as a public health
crisis of global concern by the World Health Organization (WHO). COVID-19 pandemic …
crisis of global concern by the World Health Organization (WHO). COVID-19 pandemic …
[HTML][HTML] Associations between the COVID-19 pandemic and hospital infrastructure adaptation and planning—a scoping review
C Ndayishimiye, C Sowada, P Dyjach… - International journal of …, 2022 - mdpi.com
The SARS-CoV-2 pandemic has put unprecedented pressure on the hospital sector around
the world. It has shown the importance of preparing and planning in the future for an …
the world. It has shown the importance of preparing and planning in the future for an …
Artificial neural network-based estimation of COVID-19 case numbers and effective reproduction rate using wastewater-based epidemiology
As a cost-effective and objective population-wide surveillance tool, wastewater-based
epidemiology (WBE) has been widely implemented worldwide to monitor the severe acute …
epidemiology (WBE) has been widely implemented worldwide to monitor the severe acute …
Genetic prediction of ICU hospitalization and mortality in COVID‐19 patients using artificial neural networks
PG Asteris, E Gavriilaki… - Journal of cellular …, 2022 - Wiley Online Library
There is an unmet need of models for early prediction of morbidity and mortality of
Coronavirus disease‐19 (COVID‐19). We aimed to a) identify complement‐related genetic …
Coronavirus disease‐19 (COVID‐19). We aimed to a) identify complement‐related genetic …
Forecasting COVID-19 recovered cases with Artificial Neural Networks to enable designing an effective blood supply chain
This study introduces a forecasting model to help design an effective blood supply chain
mechanism for tackling the COVID-19 pandemic. In doing so, first, the number of people …
mechanism for tackling the COVID-19 pandemic. In doing so, first, the number of people …
[HTML][HTML] A comprehensive and integrated hospital decision support system for efficient and effective healthcare services delivery using discrete event simulation
The difficulty that hospital management has been experiencing over the past decade in
balancing demand and capacity needs is unprecedented in the United Kingdom. Due to a …
balancing demand and capacity needs is unprecedented in the United Kingdom. Due to a …
[HTML][HTML] Trends and hot topics in radiology, nuclear medicine and medical imaging from 2011–2021: a bibliometric analysis of highly cited papers
S Yan, H Zhang, J Wang - Japanese Journal of Radiology, 2022 - Springer
Purpose To spotlight the trends and hot topics looming from the highly cited papers in the
subject category of Radiology, Nuclear Medicine & Medical Imaging with bibliometric …
subject category of Radiology, Nuclear Medicine & Medical Imaging with bibliometric …
[HTML][HTML] Forecasting ward-level bed requirements to aid pandemic resource planning: Lessons learned and future directions
MR Johnson, H Naik, WS Chan, J Greiner… - Health Care …, 2023 - Springer
During the COVID-19 pandemic, there has been considerable research on how regional
and country-level forecasting can be used to anticipate required hospital resources. We add …
and country-level forecasting can be used to anticipate required hospital resources. We add …
[HTML][HTML] Wastewater-based epidemiology for COVID-19 using dynamic artificial neural networks
Global efforts in vaccination have led to a decrease in COVID-19 mortality but a high
circulation of SARS-CoV-2 is still observed in several countries, resulting in some cases of …
circulation of SARS-CoV-2 is still observed in several countries, resulting in some cases of …
Decision-making algorithm and predictive model to assess the impact of infectious disease epidemics on the healthcare system: the COVID-19 case study in Italy
To improve decision-making strategies and prediction based on epidemiological data, so far
biased by highly-variable criteria, algorithms using unbiased morbidity parameters, ie …
biased by highly-variable criteria, algorithms using unbiased morbidity parameters, ie …