WCSE

Risk Analysis and Prediction of Covid-19 Infection Using Machine Learning Techniques

Abstract—Coronavirus (COVID-19), the lethal contagious virus which has caused a pandemic, has metastasized all over the world starting from China. The figures observed of the number of casualties, is in millions and billions. This new malicious virus has caused panic amongst pubic, implanted fear and number of doubts in people’s minds. There is lack of information as scientists are working on eradicating this deadly virus, less information has instilled doubts and people are panicking being helpless about how to cope up with the virus. Ways to protect oneself from getting infected, how could and where could one seek medical help when needed, these kinds of queries should be sorted out and the public needs to be educated about the virus. This will help calm down the public. This would also aid in keeping tranquil environment and even help in health and government sector workers to carry on with their duties without any obstacles.

Index Terms—global pandemic, coronavirus (COVID-19), Asymptomatic; symptoms, diagnosis, prognosis, k-means, naïve bayes, Support Vector Machine (SVM), K-Nearest Neighbor (KNN), self-assessment, posterior probability

H L Gururaj
Department of CSE, Vidyavardhaka College of Engineering, Mysuru, Karnataka, INDIA
Hong Lin
Department of CS, University of Houston, Downtown, USA
B R Sunil Kumar, Janhavi V
Department of CSE, Vidyavardhaka College of Engineering, Mysuru, Karnataka, INDIA
Manu M N
Department of ISE, SJBIT, Bengaluru, Karnataka, INDIA

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Cite: H L Gururaj, Hong Lin, B R Sunil Kumar, Janhavi V, Manu M N, "Risk Analysis and Prediction of Covid-19 Infection Using Machine Learning Techniques, " Proceedings of 2022 the 12th International Workshop on Computer Science and Engineering (WCSE 2022), pp. 137-145, June 24-27, 2022.