Conference proceedings article
Severity Prediction of COVID-19 Patients Using Machine Learning Classification Algorithms: A Case Study of Small City in Pakistan with Minimal Health Facility


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Author list: Hina Gull, Gomathi Krishna, May Issa Aldossary, and Sardar Zafar Iqbal
Publication year: 2021
Start page: 1537
End page: 1541
Number of pages: 5
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Scopus ID: 85101721763


Coronavirus disease has been declared as an infectious pandemic affecting the life and health of millions across the globe. It has caused high number of mortalities giving birth to exceptional state of emergency worldwide. It has not affected the people but also has damaged infrastructure of different countries, especially causing an exceptional situation in health care systems globally. Due to unavailability of vaccination and faster human to human transmission of virus, healthcare facilities are at high risk of exceeding their limit and capacity, especially in developing countries like Pakistan. Therefore, it is important to manage resources properly in these countries to control high mortality rate and damage it can cause. In this paper we have taken a case study of small city in Pakistan, where healthcare facilities are not enough to deal with pandemic. Most of the COVID-19 patients have to be refer to big cities based on their severity. We have taken data of COVID-19 positive patients from this small city, developed and applied machine learning classification model to predict the severity of patient, in order to deal with the shortage of resources. Among all seven taken and tested algorithms, we have chosen SVM to predict severity of patients. Model has shown 60% of accuracy and have divided patient's severity into mild, moderate and severe levels.


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Last updated on 2021-08-04 at 14:06