Machine learning approaches towards predicting risk factors of COVID-19 patients

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Covid-19 is a severe infectious disease caused by SARS-COV-2 virus. This virus can be transmitted by infected persons breathing, coughing and sneezing. By March 2022, around 444 million people have been infected with the virus and around 6 million people have died because of this. As this is our modern day global pandemic, people have suffered because of it all over the world. Coronavirus can affect our respiratory system and it can severely damage our res piratory organs and blood vessels. Every coronavirus test in the world is conducted by testing droplets from our respiratory organs like the throat and nose. Although these tests show if the person is infected or not there is no test for the severity of this disease but we can get an idea about these by a complete blood test. Coronavirus can affect our blood circulation and as a result there could be some altercation in our blood stream. In our project we identified some irregularities in the covid-19 infected blood counts and it can give us some indications about how severe the infec tion has spread. Apart from the blood count we have considered simple medication and ventilation provided to the patient to our program to determine how severe the infection is and their chances of survival. We will discuss the methods of two similar projects like ours who used machine learning to identify or determine the severity of covid-19 patients. As we used decision tree for our project, these projects used different methods and they had better access to medical data and funding.
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Electrical and Computer Engineering
North South University
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