Application of machine learning for the diagnosis of COVID-19

ABSTRACT: This chapter focuses on the application of machine learning algorithms on the diagnosis of the novel coronavirus disease (COVID-19). First, data visualization is provided on increases in confirmed deaths and recovered cases of COVID-19 using currently available data from Johns Hopkins University. Next, the machine learning algorithms are used for the automatic diagnosis of COVID-19. Data-driven diagnosis is performed using a dataset of 5644 samples with 111 attributes provided by Hospital Israelita Albert Einstein, Brazil. As a preprocessing step, null values and categorical data are processed and standardization is performed. Next, feature selection is performed to find attributes that are most important for a COVID-19 diagnosis. A number of algorithms including random forest logistic reg

SUBMITTER: Podder P 

PROVIDER: S-EPMC8137818 | biostudies-literature | 2021 Jan

REPOSITORIES: biostudies-literature