A comprehensive review of machine learning used to combat covid-19

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SUMMARY

    To train such accurate models, machine_learning algorithms need access to huge datasets. In this review, the authors summarize some of the machine_learning architectures that have been successful at an accurate diagnosis of COVID-19 using primarily CT imaging datasets. Based on the existing literature presented in research similar to, the authors primarily focused on machine_learning models developed and published in the years 2021, and 2022. The diagnostic models are primarily focused on deep learning while the prognostic and longitudinal study explores machine_learning. SVM is a supervised learning method in machine_learning that is used for . . .

     

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