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[HTML][HTML] Machine learning, deep learning, and mathematical models to analyze forecasting and epidemiology of COVID-19: a systematic literature review
COVID-19 is a disease caused by SARS-CoV-2 and has been declared a worldwide
pandemic by the World Health Organization due to its rapid spread. Since the first case was …
pandemic by the World Health Organization due to its rapid spread. Since the first case was …
Using simulation modelling and systems science to help contain COVID‐19: A systematic review
This study systematically reviews applications of three simulation approaches, that is,
system dynamics model (SDM), agent‐based model (ABM) and discrete event simulation …
system dynamics model (SDM), agent‐based model (ABM) and discrete event simulation …
Predicting coronary heart disease using an improved LightGBM model: Performance analysis and comparison
H Yang, Z Chen, H Yang, M Tian - IEEE Access, 2023 - ieeexplore.ieee.org
Coronary heart disease (CHD) is a dangerous condition that cannot be completely cured.
Accurate detection of early coronary artery disease can assist physicians in treating patients …
Accurate detection of early coronary artery disease can assist physicians in treating patients …
Why do we need agent-based macroeconomics?
We are entering the third decade of the twenty-first century with profound uncertainties and
crucial challenges for the world economy. Phenomena like climate change, digital …
crucial challenges for the world economy. Phenomena like climate change, digital …
Mean field game for modeling of COVID-19 spread
V Petrakova, O Krivorotko - Journal of Mathematical Analysis and …, 2022 - Elsevier
The paper presents one of the possible approaches to pandemic spread modeling. The
proposed model is based on the mean-field control inside separate groups of population …
proposed model is based on the mean-field control inside separate groups of population …
Agent-based mathematical model of COVID-19 spread in Novosibirsk region: Identifiability, optimization and forecasting
O Krivorotko, M Sosnovskaia… - Journal of Inverse and Ill …, 2023 - degruyter.com
The problem of identification of unknown epidemiological parameters (contagiosity, the
initial number of infected individuals, probability of being tested) of an agent-based model of …
initial number of infected individuals, probability of being tested) of an agent-based model of …
How information propagation in hybrid spaces affects decision-making: using abm to simulate covid-19 vaccine uptake
The notion of physical space has long been central in geographical theories. However, the
widespread adoption of information and communication technologies (ICTs) has freed …
widespread adoption of information and communication technologies (ICTs) has freed …
Agent-based simulation for infectious disease modelling over a period of multiple days, with application to an airport scenario
T Harweg, M Wagner, F Weichert - International Journal of Environmental …, 2022 - mdpi.com
With the COVID-19 pandemic, the role of infectious disease spreading in public places has
been brought into focus more than ever. Places that are of particular interest regarding the …
been brought into focus more than ever. Places that are of particular interest regarding the …
[HTML][HTML] Heterogeneity is a key factor describing the initial outbreak of COVID-19
Assessing the transmission potential of emerging infectious diseases, such as COVID-19, is
crucial for implementing prompt and effective intervention policies. The basic reproduction …
crucial for implementing prompt and effective intervention policies. The basic reproduction …
How artificial intelligence cooperating with agent‐based modeling for urban studies: A systematic review
As urbanization accelerates, cities become more complex, coming along with more complex
urban issues. Agent‐based model (ABM) is a traditional method to simulate activities in a …
urban issues. Agent‐based model (ABM) is a traditional method to simulate activities in a …