Personification and Safety during pandemic of COVID19 using Machine Learning

ABSTRACT

COVID19 is a respiratory disease and World health organization [WHO] has classified this disease as pandemic because of its high mortality rates among people with poor medical history conditions. It is important to identify such individuals, who are not safe and to avoid severe complications if get exposed to COVID19. There is no system, which can alert the person based on his health condition. Proposing a machine learning approach would help to achieve safety, personification and mitigate the effects of COVID19 disease. In presence of scarcity of information about COVID19 for the purposes of model building is a key challenge. Proposed research used natural language embedded media data information maintained in hospitals about respiratory diseases and used this information to identify the individuals who can be not safe if exposed to COVID19 patients. The proposed approach will provide an intuitive way to understand the risk of being getting affected based on the immunization of respiratory system of an individual. The risk factor will provide a basis for personification and to take safety measures in this long lasting pandemic situation. © 2020 IEEE.