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      • A new SEAIRD pandemic prediction model with clinical and epidemiological data analysis on COVID-19 outbreak 

        Liu, Xian-Xian; Fong, Simon James; Dey, Nilanjan; González-Crespo, Rubén ; Herrera-Viedma, Enrique (Applied intelligence, 2021)
        Measuring the spread of disease during a pandemic is critically important for accurately and promptly applying various lockdown strategies, so to prevent the collapse of the medical system. The latest pandemic of COVID-19 ...
      • Modelling dynamics of coronavirus disease 2019 spread for pandemic forecasting based on Simulink 

        Liu, Xian-Xian; Hu, Shimin; Fong, Simon James; González-Crespo, Rubén ; Herrera-Viedma, Enrique (Physical biology, 2021)
        In this paper, we demonstrate the application of MATLAB to develop a pandemic prediction system based on Simulink. The susceptible-exposed-asymptomatic but infectious-symptomatic and infectious (severe infected population ...
      • The Application of Supervised and Unsupervised Computational Predictive Models to Simulate the COVID19 Pandemic 

        James Fong, Simon; Lobo Marques, João Alexandre; Li, G.; Dey, Nilanjan; González-Crespo, Rubén; Herrera-Viedma, Enrique; Bernardo Gois, F. Nauber; Xavier Neto, José (Epidemic Analytics for Decision Supports in COVID19 Crisis, 2022)
        The application of different tools for predicting COVID19 cases spreading has been widely considered during the pandemic. Comparing different approaches is essential to analyze performance and the practical support they ...

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