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Subgroup classification model identifying the most influential factors in the mortality of patients with COVID-19 using data analysis

Abstract:

This research assesses the health conditions of the people in the study and determines the reason why a person dies after being infected with COVID-19. In this study, 538 sample groups that provided medical data from people in different locations were analyzed. The biggest challenge in this study was to carry out 2 different criteria within the same data set to conclude that the mortality of the persons inside a group depends more than anything on the age of the person at risk and the presence of one or more other health disorders of the primary disease, which in this case is COVID-19. For this study, the public data set 'COVID analytics' was used, which provided all the necessary medical information and the classification of the groups, which are then interpreted as useful labels to better deduce the degree of mortality of the affected person. After completing the data analysis, it is determined that the factors that aggravate the condition of a patient with COVID-19 are: hypertension, advanced age and any other disease.