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Paper Details


Title
Predicting Covid-19 Test Report Using Data Mining Techniques Based on The Second Wave in Bangladesh
Author
Md. Asif Mahmud Ridoy, Abdus Sattar, Dr. Fizar Ahmed, Md. Fahim Sarker, Shuvo Datta,
Email
Abstract
Coronavirus (Covid-19) is a disease that spreads from one person to another very quickly. The whole world is facing this Covid-19 pandemic now and Bangladesh is also not out of it. After the first wave, now the second wave is going on in Bangladesh. As the second wave is spreading faster than the first wave and the test process of Covid-19 is very time-consuming. As a result, before getting the test report, a person infected with Covid-19 and spreads this virus to other people as he doesn't know whether he is infected with Coronavirus or not. To create a dataset, we have asked some patients from our nearby people who live in Faridpur, Joypurhat, and Cumilla district and collected their data who have tested for Covid-19 during the second wave. We have collected some of their symptoms that appeared before their Covid-19 test. With this dataset, we have used some data mining approach to predict whether a patient is tested positive or negative. We have applied two algorithms here. Among them, Naive Bayes gives the highest accuracy which is 80%.

Keywords
Data Mining , Data Exploration , Naive Bayes , k nearest neighbors , prediction , comparison
Journal or Conference Name
2021 12th International Conference on Computing Communication and Networking Technologies (ICCCNT)
Publication Year
2021
Indexing
scopus