Abstract
In December 2019, the COVID-19 rapidly infected virus disease was an outbreak in China. Woefully, the number of infected and death cases is increasing day after day. Still, there is no effective vaccine and antibiotic. As a result, our fighting starts with an invisible enemy. Up to July 31, 2020 the total number of death cases is 3111 (Male: 2446 and Female: 665), infected cases are 237,661, and recovered cases are 135,136 in Bangladesh. The most infected city is Dhaka with 47.83% death cases. Among our overall population, senior citizens and infants are more valuable assets for the nation. In this research work, the K-means algorithm was implemented to discover a pattern from collected data with the help of a data mining technique to predict the age level for death cases on COVID-19. Data were collected from 8 March 2020 to 31 July 2020 from authentic recognized sources. In this research work, R language is used for clustering on the K-means algorithm. The result analysis of this research shows that the most infected age range is above 60 years in this period, and they have a high possibility of death cases in the near future.
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Hoque, M.A., Islam, T., Amin, A., Ahmed, T. (2021). Clustering-Based Pattern Analysis on COVID-19 Using K-Means Algorithm to Predict the Death Cases in Bangladesh. In: Shakya, S., Balas, V.E., Haoxiang, W., Baig, Z. (eds) Proceedings of International Conference on Sustainable Expert Systems. Lecture Notes in Networks and Systems, vol 176. Springer, Singapore. https://doi.org/10.1007/978-981-33-4355-9_51
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