ankushmallick1100 / A-COVID-19-Infection-Rate-Detection-Technique-Using-Bayes-Probability

A COVID-19 Infection Rate Detection Technique Using Bayes Probability

A COVID-19 Infection Rate Detection Technique Using Bayes Probability

The main objective of this paper is to detect the infection rate of the SARS-Cov-2 virus among patients who are suffering from COVID with different symptoms. In this work, some data inputs from the intended patients (like contact with any COVID infected person and any COVID patient within 1 km.) are collected in the form of a questionnaire and then applied Naïve Bayes probabilistic technique to evaluate the probability of how much that patient is affected in this deadly virus. Following this process, we collect sample data of 80 patients and apply the proposed analysis process using the C programming language. This approach also shows the comparison for different test cases with respect to the feedbacks of actual patient data analysis.

Link of the paper: https://link.springer.com/chapter/10.1007/978-981-19-4052-1_57