Data Mining Techniques for Pandemic Outbreak in Healthcare

Pandemic outbreaks such as SARS-CoV, MERS-CoV and Covid-19 have attracted worldwide attention since these viruses affected many countries become a global public health issue. In 2019, was announced pandemic disease categorized emergency globally. It is ranked the sixth most serious internationally. This tracking analysis require an appropriate method that gives better performance in terms of accuracy, precision recall defines its pattern it involves huge complicated datasets from pandemic. Pattern identification currently applied instances due to rapid growth data besides having potential generate knowledge-rich environment which can help significantly improve quality clinical decisions identify relationships between items. Therefore, there need review techniques mining on outbreak focuses healthcare. The goal this study analyze algorithms had been implemented for past research Covid-19. result shows 2 main algorithms, namely Naïve Bayes Decision Tree, classification method, are give more than 90% accuracy both will be further considered investigated future large researchers healthcare practitioners controlling infection coronavirus using technique discussed.