Application of machine learning in the prediction of COVID-19 daily new cases: A scoping review
Soudeh Ghafouri‐Fard, Hossein Mohammad‐Rahimi, Parisa Motie, Mohammad A.S. Minabi, Mohammad Taheri, Saeedeh Nateghinia
Abstract
values near 1. ARIMA and LSTM had the highest MAPE values. Collectively, these models are capable of identification of learning parameters that affect dissimilarities in COVID-19 spread across various regions or populations, combining numerous intervention methods and implementing what-if scenarios by integrating data from diseases having analogous trends with COVID-19. Therefore, application of these methods would help in precise policy making to design the most appropriate interventions and avoid non-efficient restrictions.
Topics & Concepts
Mean absolute percentage errorMean squared errorAutoregressive integrated moving averageAdaptive neuro fuzzy inference systemArtificial intelligenceArtificial neural networkMachine learningMultilayer perceptronPerceptronComputer scienceStatisticsFuzzy logicData miningTime seriesFuzzy control systemMathematicsCOVID-19 epidemiological studiesCOVID-19 diagnosis using AISARS-CoV-2 and COVID-19 Research