Using data mining techniques deep analysis and theoretical investigation of COVID-19 pandemic.

This study uses K-Means Clustering to analyze Corona-Virus Diseases (Covid-19). Data mining in medicine has generated novel approaches to examine diseases. Coronavirus is difficult to treat because of its intricate structure, shape, and texture. Due to data mining improvements, the K-Means approach has been developed for evaluating covid-19. Observe the outbreak's evolution, including its peak, and containment measures. A basic K-Means model is used to simulate Coronavirus's prevalence in Iraq. Pandemic-prevention efforts may slow its spread. If inhibition grows to 50%, Iraq will have 500,000 patients by year's end. If precautions were halved, the number would top 1 million. If we abandon all measures, the sickness will worsen. In that case, 55% of the population may be affected by the end of the month. This number will drop after September.

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The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.