Predicting the Vulnerability of Covid-19 using Machine Learning Algorithm

Abstract

In this research, a quantitative model is developed to predict people's susceptibility to Covid-19 supported by their comorbid diseases and factors associated with Covid19. Researchers have found that individuals with comorbid diseases have higher chance of being infected and developing more severe Covid-19 conditions. However, these patterns are only observed through correlational analyses between patient phenotypes and the severity of their Covid-19 infection. The research reported in this paper presents a comprehensive approach to determine the impact of pre-existing disorders on Covid-19. This might be substantiated by a complete study of the patient level dataset, which includes their prior conditions, vital health information, and age group, as well as the influence of Covid-19 on them. The analysis revolves around how each disease affects a patient's immunity, which includes endpoints such as admission of patients to a regular ward, semi-ICU, or ICU. Monitoring the patient's current conditions, supports the final outcome.